"ACF" <-
structure(list(INJECTION = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3), TIME = c(6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 12, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24, 24, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 
6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 24, 24, 24), SECTION = c(1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 
5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 
5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 
5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 
5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 
5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 
5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 
5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 
5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 
5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6, 1, 
2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6), TOTAL = c(35, 19, 21, 8, 3, 
1, 7, 12, 13, 6, 12, 3, 9, 25, 7, 8, 18, 5, 19, 15, 19, 25, 9, 
3, 12, 32, 18, 12, 2, 2, 19, 11, 29, 19, 5, 2, 6, 15, 18, 28, 
11, 5, 16, 40, 32, 41, 12, 0, 20, 17, 14, 9, 18, 4, 18, 13, 7, 
32, 37, 2, 34, 43, 28, 23, 3, 0, 32, 46, 22, 29, 54, 6, 38, 46, 
23, 51, 42, 13, 22, 22, 66, 42, 37, 4, 37, 19, 62, 60, 13, 0, 
63, 29, 56, 35, 19, 7, 32, 40, 57, 58, 19, 1, 55, 60, 15, 37, 
42, 7, 34, 23, 26, 17, 6, 0, 61, 86, 44, 73, 19, 1, 140, 48, 
100, 57, 8, 0, 39, 40, 40, 43, 5, 0, 14, 31, 30, 16, 25, 10, 
13, 18, 15, 20, 15, 3, 10, 12, 28, 16, 32, 2, 22, 10, 19, 44, 
23, 13, 26, 43, 35, 34, 6, 0, 32, 34, 36, 20, 2, 0, 17, 14, 13, 
19, 16, 5, 15, 7, 24, 8, 22, 10, 60, 79, 103, 99, 68, 6, 46, 
28, 42, 27, 26, 2, 11, 15, 37, 27, 26, 19, 47, 83, 77, 51, 11, 
0, 37, 53, 74, 45, 6, 3, 98, 116, 100, 21, 2, 0, 74, 102, 111, 
49, 6, 0, 23, 22, 26, 10, 14, 0, 89, 92, 105, 77, 104, 42, 48, 
78, 121, 82, 79, 15, 28, 68, 52, 46, 73, 14, 108, 124, 92, 32, 
37, 83, 81, 85, 70, 125, 100, 0, 132, 125, 62, 65, 13, 4, 28, 
46, 70, 45, 57, 8, 67, 92, 85, 41, 14, 6, 21, 18, 21, 37, 44, 
24, 32, 15, 13, 11, 9, 8, 21, 20, 14, 25, 40, 23, 27, 36, 31, 
31, 31, 16, 38, 38, 34, 34, 18, 5, 8, 6, 9, 29, 17, 18, 18, 36, 
59, 43, 15, 17, 32, 47, 54, 64, 64, 32, 17, 18, 18, 9, 11, 15, 
26, 45, 78, 101, 50, 35, 46, 52, 90, 68, 130, 36, 15, 23, 15, 
24, 27, 25, 17, 34, 43, 9, 48, 21, 35, 51, 53, 88, 65, 12, 15, 
39, 58, 56, 58, 26, 61, 68, 79, 124, 121, 51, 95, 93, 80, 123, 
146, 33, 83, 91, 115, 65, 99, 13, 54, 149, 133, 150, 159, 15, 
62, 65, 55, 146, 213, 84), AVERAGE = c(2.11428571428571, 2.10526315789474, 
1.71428571428571, 1.25, 1, 1, 2.42857142857143, 2.83333333333333, 
2.30769230769231, 1.16666666666667, 2.16666666666667, 1, 2.44444444444444, 
2, 2.57142857142857, 2, 1.83333333333333, 1, 2.05263157894737, 
1.6, 1.84210526315789, 1.96, 1.66666666666667, 1.66666666666667, 
3.25, 2.84375, 2.27777777777778, 3.16666666666667, 1.5, 1, 3.57894736842105, 
2.27272727272727, 1.89655172413793, 1.52631578947368, 1.4, 1.5, 
1, 1.13333333333333, 1.66666666666667, 2.21428571428571, 2.27272727272727, 
2, 1.8125, 1.925, 1.84375, 2.02439024390244, 2.41666666666667, 
NA, 1.9, 2.11764705882353, 2.21428571428571, 2.11111111111111, 
2.44444444444444, 3.75, 2, 2.30769230769231, 1.42857142857143, 
1.59375, 2.21621621621622, 1, 2.14705882352941, 2.23255813953488, 
2.14285714285714, 1.91304347826087, 1, NA, 2.15625, 2.23913043478261, 
2.68181818181818, 1.93103448275862, 2, 2, 2.13157894736842, 1.89130434782609, 
1.95652173913043, 2.07843137254902, 2.11904761904762, 1.46153846153846, 
1.90909090909091, 2.22727272727273, 2, 2.14285714285714, 2.02702702702703, 
1.25, 1.72972972972973, 2.31578947368421, 2.17741935483871, 1.98333333333333, 
1.38461538461538, NA, 1.66666666666667, 1.44827586206897, 1.53571428571429, 
1.54285714285714, 1.52631578947368, 1.28571428571429, 1.8125, 
1.85, 1.94736842105263, 2, 1.89473684210526, 1, 1.81818181818182, 
2.1, 1.86666666666667, 1.67567567567568, 1.5, 1.14285714285714, 
1.35294117647059, 1.56521739130435, 1.46153846153846, 1.64705882352941, 
1.16666666666667, NA, 1.55737704918033, 1.90697674418605, 1.93181818181818, 
2.10958904109589, 1.89473684210526, 1, 1.74285714285714, 1.83333333333333, 
1.91, 1.87719298245614, 1.375, NA, 1.66666666666667, 1.95, 1.4, 
1.58139534883721, 1.2, NA, 2.85714285714286, 2.7741935483871, 
2.86666666666667, 1.9375, 1.96, 2.2, 1.76923076923077, 2.72222222222222, 
2.66666666666667, 1.95, 2.4, 1.66666666666667, 2.1, 3.33333333333333, 
1.85714285714286, 1.4375, 1.96875, 1, 2.59090909090909, 2, 1.73684210526316, 
2, 2.34782608695652, 2.15384615384615, 3.65384615384615, 3, 2.22857142857143, 
2.38235294117647, 1.5, NA, 3.03125, 2.52941176470588, 2.86111111111111, 
2.25, 2, NA, 2.29411764705882, 2.64285714285714, 2.92307692307692, 
2.36842105263158, 2.625, 1.2, 3.46666666666667, 2.57142857142857, 
2.875, 2.125, 2.72727272727273, 2.4, 3.75, 3.20253164556962, 
3.96116504854369, 3.86868686868687, 4.19117647058824, 1.16666666666667, 
2.3695652173913, 2.92857142857143, 3.0952380952381, 2.51851851851852, 
2.26923076923077, 1, 3.63636363636364, 2.46666666666667, 3.89189189189189, 
2.51851851851852, 3.07692307692308, 3.26315789473684, 2.70212765957447, 
3.02409638554217, 2.7012987012987, 2.80392156862745, 1.72727272727273, 
NA, 3.08108108108108, 3.0188679245283, 3.01351351351351, 4.15555555555556, 
2.5, 1.33333333333333, 3.38775510204082, 3.05172413793103, 3.05, 
2.14285714285714, 2, NA, 2.72972972972973, 2.61764705882353, 
2.74774774774775, 3.08163265306122, 1.16666666666667, NA, 4.26086956521739, 
2.72727272727273, 3, 4.2, 3.64285714285714, NA, 1.8314606741573, 
1.96739130434783, 1.84761904761905, 1.94805194805195, 2.11538461538462, 
2.23809523809524, 2.125, 2.53846153846154, 2.47933884297521, 
2.39024390243902, 2.32911392405063, 1.33333333333333, 2.64285714285714, 
2.16176470588235, 2.38461538461538, 2.6304347826087, 2.84931506849315, 
1.64285714285714, 2.98148148148148, 2.80645161290323, 2.65217391304348, 
3.21875, 3.24324324324324, 3.7710843373494, 3.12345679012346, 
3.07058823529412, 3.04285714285714, 4, 4.02, NA, 2.56818181818182, 
2.264, 2.58064516129032, 2.56923076923077, 2.30769230769231, 
1.5, 2.78571428571429, 3.04347826086957, 2.81428571428571, 2.86666666666667, 
3.80701754385965, 2.25, 3.16417910447761, 3.82608695652174, 3.51764705882353, 
4.17073170731707, 2.28571428571429, 1.5, 2.19047619047619, 2.61111111111111, 
2.23809523809524, 2.43243243243243, 2.15909090909091, 2.25, 2.59375, 
2.4, 2.61538461538462, 3.36363636363636, 3.11111111111111, 1.375, 
2.23809523809524, 3.15, 2.85714285714286, 3.2, 2.425, 2.56521739130435, 
2.74074074074074, 3.88888888888889, 3.03225806451613, 2.7741935483871, 
3.09677419354839, 2.6875, 2, 2.18421052631579, 2.35294117647059, 
2.05882352941176, 2.66666666666667, 1, 2.75, 2.83333333333333, 
3.55555555555556, 2.68965517241379, 4.58823529411765, 2.27777777777778, 
2.83333333333333, 2.97222222222222, 2.91525423728814, 3.32558139534884, 
2.8, 2.11764705882353, 2.125, 2.34042553191489, 2.88888888888889, 
2.390625, 2.65625, 2.78125, 2.70588235294118, 3.38888888888889, 
2.22222222222222, 1.66666666666667, 1.09090909090909, 2.33333333333333, 
2.84615384615385, 2.73333333333333, 2.58974358974359, 2.59405940594059, 
3.76, 3.37142857142857, 3.10869565217391, 4.38461538461539, 4.23333333333333, 
4.83823529411765, 3.5, 3.16666666666667, 2.4, 2.39130434782609, 
2.8, 2.16666666666667, 2.51851851851852, 2.32, 2.88235294117647, 
3.91176470588235, 3.3953488372093, 7.33333333333333, 4.08333333333333, 
4.80952380952381, 2.91428571428571, 3.84313725490196, 3.56603773584906, 
2.88636363636364, 3, 1.41666666666667, 2.33333333333333, 3.25641025641026, 
3.1551724137931, 3.05357142857143, 3.43103448275862, 2.57692307692308, 
3.63934426229508, 3.85294117647059, 5.40506329113924, 4.06451612903226, 
3.32231404958678, 4.41176470588235, 2.32631578947368, 2.60215053763441, 
2.675, 2.71544715447154, 2.58904109589041, 3.15151515151515, 
3.14457831325301, 5.45054945054945, 6.25217391304348, 3.63076923076923, 
3.38383838383838, 1.61538461538462, 2.22222222222222, 3.06040268456376, 
3.19548872180451, 3.17333333333333, 2.83647798742138, 1.66666666666667, 
2.25806451612903, 2.23076923076923, 2.50909090909091, 2.82876712328767, 
3.13145539906103, 3.21428571428571)), .Names = c("INJECTION", 
"TIME", "SECTION", "TOTAL", "AVERAGE"), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
"47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", 
"58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", 
"69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79", 
"80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90", 
"91", "92", "93", "94", "95", "96", "97", "98", "99", "100", 
"101", "102", "103", "104", "105", "106", "107", "108", "109", 
"110", "111", "112", "113", "114", "115", "116", "117", "118", 
"119", "120", "121", "122", "123", "124", "125", "126", "127", 
"128", "129", "130", "131", "132", "133", "134", "135", "136", 
"137", "138", "139", "140", "141", "142", "143", "144", "145", 
"146", "147", "148", "149", "150", "151", "152", "153", "154", 
"155", "156", "157", "158", "159", "160", "161", "162", "163", 
"164", "165", "166", "167", "168", "169", "170", "171", "172", 
"173", "174", "175", "176", "177", "178", "179", "180", "181", 
"182", "183", "184", "185", "186", "187", "188", "189", "190", 
"191", "192", "193", "194", "195", "196", "197", "198", "199", 
"200", "201", "202", "203", "204", "205", "206", "207", "208", 
"209", "210", "211", "212", "213", "214", "215", "216", "217", 
"218", "219", "220", "221", "222", "223", "224", "225", "226", 
"227", "228", "229", "230", "231", "232", "233", "234", "235", 
"236", "237", "238", "239", "240", "241", "242", "243", "244", 
"245", "246", "247", "248", "249", "250", "251", "252", "253", 
"254", "255", "256", "257", "258", "259", "260", "261", "262", 
"263", "264", "265", "266", "267", "268", "269", "270", "271", 
"272", "273", "274", "275", "276", "277", "278", "279", "280", 
"281", "282", "283", "284", "285", "286", "287", "288", "289", 
"290", "291", "292", "293", "294", "295", "296", "297", "298", 
"299", "300", "301", "302", "303", "304", "305", "306", "307", 
"308", "309", "310", "311", "312", "313", "314", "315", "316", 
"317", "318", "319", "320", "321", "322", "323", "324", "325", 
"326", "327", "328", "329", "330", "331", "332", "333", "334", 
"335", "336", "337", "338", "339", "340", "341", "342", "343", 
"344", "345", "346", "347", "348", "349", "350", "351", "352", 
"353", "354", "355", "356", "357", "358", "359", "360", "361", 
"362", "363", "364", "365", "366", "367", "368", "369", "370", 
"371", "372", "373", "374", "375", "376", "377", "378", "379", 
"380", "381", "382", "383", "384", "385", "386", "387", "388", 
"389", "390", "391", "392", "393", "394", "395", "396"))
"Cars93.summary" <-
structure(list(Min.passengers = c(4, 6, 4, 4, 2, 7), Max.passengers = c(6, 
6, 6, 5, 4, 8), No.of.cars = structure(c(16, 11, 22, 21, 14, 
9), .Names = c("Compact", "Large", "Midsize", "Small", "Sporty", 
"Van")), abbrev = c("C", "L", "M", "Sm", "Sp", "V")), .Names = c("Min.passengers", 
"Max.passengers", "No.of.cars", "abbrev"), row.names = c("Compact", 
"Large", "Midsize", "Small", "Sporty", "Van"), class = "data.frame")
"additions" <-
function(objnames = dsetnames)
{
	newnames <- objects()
	existing <- as.logical(match(newnames, objnames, nomatch = 0))
	newnames[!existing]
}
"ais" <-
structure(list(rcc = c(3.96, 4.41, 4.14, 4.11, 4.45, 4.1, 4.31, 
4.42, 4.3, 4.51, 4.71, 4.62, 4.35, 4.26, 4.63, 4.36, 3.91, 4.51, 
4.37, 4.9, 4.46, 3.95, 4.46, 5.02, 4.26, 4.46, 4.16, 4.49, 4.21, 
4.57, 4.87, 4.44, 4.45, 4.41, 4.87, 4.56, 4.15, 4.16, 4.32, 4.06, 
4.12, 4.17, 3.8, 3.96, 4.44, 4.27, 3.9, 4.02, 4.39, 4.52, 4.25, 
4.46, 4.4, 4.83, 4.23, 4.24, 3.95, 4.03, 4.36, 4.07, 4.17, 4.23, 
4.46, 4.38, 4.31, 4.51, 4.13, 4.48, 5.31, 4.58, 4.81, 4.51, 4.77, 
5.33, 4.75, 4.11, 4.76, 4.27, 4.44, 4.2, 4.71, 4.09, 4.24, 3.9, 
4.82, 4.32, 4.77, 5.16, 4.97, 4, 4.4, 4.38, 4.08, 4.98, 5.16, 
4.66, 4.19, 4.53, 4.09, 4.42, 5.13, 4.83, 5.09, 5.17, 5.11, 5.03, 
5.32, 4.75, 5.34, 4.87, 5.33, 4.81, 4.32, 4.87, 5.04, 4.4, 4.95, 
4.78, 5.21, 5.22, 5.18, 5.4, 4.92, 5.24, 5.09, 4.83, 5.22, 4.71, 
5.24, 4.54, 5.13, 5, 5.17, 4.89, 4.5, 4.84, 4.13, 4.87, 4.82, 
4.73, 4.55, 4.71, 4.93, 5.21, 5.09, 5.11, 4.94, 4.87, 4.41, 4.86, 
4.91, 4.93, 4.2, 5.1, 4.5, 4.89, 5.13, 4.88, 5, 5.48, 5.93, 5.01, 
5.48, 5.16, 4.64, 6.72, 4.83, 5.34, 5.13, 4.68, 5, 4.99, 5.49, 
5.59, 5.03, 5.5, 5.11, 4.96, 5.01, 5.11, 5.69, 4.63, 4.91, 4.95, 
5.34, 5.16, 5.29, 5.02, 5.01, 5.03, 5.25, 5.08, 5.04, 4.63, 5.11, 
5.34, 4.86, 4.9, 5.66, 5.03, 4.97, 5.38), wcc = c(7.5, 8.3, 5, 
5.3, 6.8, 4.4, 5.3, 5.7, 8.9, 4.4, 5.3, 7.3, 7.8, 6.2, 6, 5.8, 
7.3, 8.3, 8.1, 6.9, 5.7, 3.3, 9.5, 6.4, 5.8, 5.6, 5.8, 7.6, 7.5, 
6.6, 6.4, 10.1, 6.6, 5.9, 7.3, 13.3, 6, 7.6, 6.4, 5.8, 6.1, 5, 
6.6, 5.5, 9.7, 10.6, 6.3, 9.1, 9.6, 5.1, 10.7, 10.9, 9.3, 8.4, 
6.9, 8.4, 6.6, 8.5, 5.5, 5.9, 4.9, 8.1, 8.3, 5.8, 5.3, 5.1, 7, 
9.5, 9.5, 5.8, 6.8, 9, 7.1, 9.3, 7.5, 7.3, 7.6, 6.9, 6.1, 6.5, 
6.9, 6.4, 6.6, 6, 7.6, 6.8, 7.2, 8.2, 7.8, 4.2, 4, 7.9, 6.6, 
6.4, 7.2, 6.4, 9, 5, 4.9, 6.4, 7.1, 7.6, 4.7, 4.1, 6.7, 7.1, 
6, 8.6, 6.6, 4.8, 5.2, 6.2, 4.3, 8.2, 7.1, 5.3, 5.9, 9.3, 6.8, 
8.4, 6.5, 6.8, 5.4, 7.5, 10.1, 5, 6, 8, 7.2, 5.9, 5.8, 6.7, 8, 
7.5, 9.2, 8.3, 8.9, 7.4, 6.4, 6.7, 5.6, 7.2, 7.3, 7.5, 8.9, 9.6, 
6.3, 6.3, 4.5, 3.9, 9, 7.3, 4.5, 6.1, 6.1, 5.8, 4, 4.3, 8.2, 
4.6, 6.4, 8.9, 6.2, 8.4, 9, 7.1, 6.6, 7.6, 4.6, 4.8, 5.2, 7.2, 
5.9, 7.9, 6.6, 6.4, 9.3, 8.3, 8.9, 8.7, 10.8, 9.1, 10.2, 7.5, 
10, 12.9, 12.7, 6.1, 9.8, 7.5, 7.4, 8.5, 6, 14.3, 7, 6.2, 8.9, 
7.6, 8.3, 6.4, 8.8, 6.3), hc = c(37.5, 38.2, 36.4, 37.3, 41.5, 
37.4, 39.6, 39.9, 41.1, 41.6, 41.4, 43.8, 41.4, 41, 43.7, 40.3, 
37.6, 43.7, 41.8, 44, 39.2, 36.9, 41.5, 44.8, 41.2, 41.1, 39.8, 
41.8, 38.4, 42.8, 44.8, 42.7, 42.6, 41.1, 44.1, 42.2, 38, 37.5, 
37.7, 38.7, 36.6, 37.4, 36.5, 36.3, 41.4, 37.7, 35.9, 37.7, 38.3, 
38.8, 39.5, 39.7, 40.4, 41.8, 38.3, 37.6, 38.4, 37.7, 41.4, 39.5, 
38.9, 38.2, 42.2, 42, 41.1, 40.9, 39.7, 36.5, 47.1, 42.1, 42.7, 
39.7, 40.6, 47, 43.8, 38.7, 42.9, 44.1, 42.6, 39.1, 43.5, 40.1, 
38.2, 38.9, 43.2, 40.6, 43.3, 45.3, 44.7, 36.6, 40.8, 39.8, 37.8, 
44.8, 44.3, 40.9, 39, 40.7, 36, 42.8, 46.8, 45.2, 46.6, 44.9, 
46.1, 45.1, 47.5, 45.5, 48.6, 44.9, 47.8, 45.2, 41.6, 43.8, 44, 
42.5, 45.4, 43, 44.5, 47.5, 45.4, 49.5, 46.2, 46.5, 44.9, 43.8, 
46.6, 45.5, 46.6, 44.4, 46.1, 45.3, 47.9, 41.6, 40.7, 46.3, 40.3, 
43.5, 44.3, 42.8, 42.6, 43.6, 46.2, 47.5, 46.3, 48.2, 45.7, 45.8, 
44.2, 44.9, 46.3, 45.2, 41.2, 45.3, 42.2, 45.5, 44.1, 45.6, 46.8, 
49.4, 49.1, 46, 48.2, 44.4, 42.9, 59.7, 43.8, 48.3, 45.3, 43, 
45.1, 41.4, 47.7, 49.7, 44.7, 48.1, 45.4, 45.3, 46, 46.5, 50.5, 
42.1, 45, 44.5, 46.8, 47.6, 48, 43.6, 46.5, 43.6, 47.3, 46.3, 
45.9, 44.8, 47.7, 49.8, 46.9, 45.6, 50.2, 42.7, 43, 46), hg = c(12.3, 
12.7, 11.6, 12.6, 14, 12.5, 12.8, 13.2, 13.5, 12.7, 14, 14.7, 
14.1, 13.9, 14.7, 13.3, 12.9, 14.7, 14.3, 14.5, 13, 12.5, 14.5, 
15.2, 14.1, 14.3, 13.3, 14.4, 13.2, 14.5, 15, 14, 14.1, 13.5, 
14.8, 13.6, 12.7, 12.3, 12.3, 12.8, 11.8, 12.7, 12.4, 12.4, 14.1, 
12.5, 12.1, 12.7, 12.5, 13.1, 13.2, 13.7, 13.6, 13.4, 12.6, 12.5, 
12.8, 13, 13.8, 13.3, 12.9, 12.7, 14.4, 14, 13.9, 14, 13.1, 13.3, 
15.9, 14.7, 15.3, 14.3, 14.6, 15, 15.2, 12.4, 13.4, 14.7, 13.9, 
13, 13.8, 13.2, 12.6, 13.5, 14.4, 13.7, 14.8, 14.7, 14.2, 12, 
13.9, 13.5, 12.1, 14.8, 14.5, 13.9, 13.4, 14, 12.5, 14.5, 15.9, 
15.2, 15.9, 15, 15.6, 15.2, 16.3, 15.2, 16.5, 15.4, 16.1, 15.3, 
14, 15, 14.8, 14.5, 15.5, 14.7, 15.4, 16.2, 14.9, 17.3, 15.8, 
15.5, 14.8, 15.1, 15.7, 15.6, 15.9, 15.6, 15.9, 15.7, 16.4, 14.4, 
13.7, 15.9, 13.5, 15, 14.8, 14.9, 14.4, 14, 15.1, 16.5, 15.4, 
16.7, 15.5, 16.1, 15, 15.4, 15.4, 15.8, 14.3, 14.9, 14.7, 15.6, 
15.2, 15.5, 14.7, 18, 16.1, 15.9, 16.3, 15.5, 14.9, 19.2, 14.3, 
16.2, 16.8, 14.8, 15.1, 14.9, 15.9, 17.2, 15.9, 16.5, 15.8, 15.7, 
15.9, 16.3, 18.5, 14.4, 15.2, 15, 16.2, 15.6, 16.2, 14.8, 15.8, 
14.4, 15.8, 15.6, 15, 15, 15.8, 17.2, 15.8, 16, 17.7, 14.3, 14.9, 
15.7), ferr = c(60, 68, 21, 69, 29, 42, 73, 44, 41, 44, 38, 26, 
30, 48, 30, 29, 43, 34, 53, 59, 43, 40, 92, 48, 77, 71, 37, 71, 
73, 85, 64, 19, 39, 41, 13, 20, 59, 22, 30, 78, 21, 109, 102, 
71, 64, 68, 78, 107, 39, 58, 127, 102, 86, 40, 50, 58, 33, 51, 
82, 25, 86, 22, 30, 27, 60, 115, 124, 54, 29, 164, 50, 36, 40, 
62, 90, 12, 36, 45, 43, 51, 22, 44, 26, 16, 58, 46, 43, 34, 41, 
57, 73, 88, 182, 80, 88, 109, 69, 41, 66, 63, 34, 97, 55, 76, 
93, 46, 155, 99, 35, 124, 176, 107, 177, 130, 64, 109, 125, 150, 
115, 89, 93, 183, 84, 70, 118, 61, 72, 91, 58, 97, 110, 72, 36, 
53, 72, 39, 61, 49, 35, 8, 106, 32, 41, 20, 44, 103, 50, 41, 
101, 73, 56, 74, 58, 87, 139, 82, 87, 80, 67, 132, 43, 212, 94, 
213, 122, 76, 53, 91, 36, 101, 184, 44, 66, 220, 191, 40, 189, 
141, 212, 97, 53, 126, 234, 50, 94, 156, 124, 87, 97, 102, 55, 
117, 52, 133, 214, 143, 65, 90, 38, 122, 233, 32), bmi = c(20.56, 
20.67, 21.86, 21.88, 18.96, 21.04, 21.69, 20.62, 22.64, 19.44, 
25.75, 21.2, 22.03, 25.44, 22.63, 21.86, 22.27, 21.27, 23.47, 
23.19, 23.17, 24.54, 22.96, 19.76, 23.36, 22.67, 24.24, 24.21, 
20.46, 20.81, 20.17, 23.06, 24.4, 23.97, 22.62, 19.16, 21.15, 
21.4, 21.03, 21.77, 21.38, 21.47, 24.45, 22.63, 22.8, 23.58, 
20.06, 23.01, 24.64, 18.26, 24.47, 23.99, 26.24, 20.04, 25.72, 
25.64, 19.87, 23.35, 22.42, 20.42, 22.13, 25.17, 23.72, 21.28, 
20.87, 19, 22.04, 20.12, 21.35, 28.57, 26.95, 28.13, 26.85, 25.27, 
31.93, 16.75, 19.54, 20.42, 22.76, 20.12, 22.35, 19.16, 20.77, 
19.37, 22.37, 17.54, 19.06, 20.3, 20.15, 25.36, 22.12, 21.25, 
20.53, 17.06, 18.29, 18.37, 18.93, 17.79, 17.05, 20.31, 22.46, 
23.88, 23.68, 23.15, 22.32, 24.02, 23.29, 25.11, 22.81, 26.25, 
21.38, 22.52, 26.73, 23.57, 25.84, 24.06, 23.85, 25.09, 23.84, 
25.31, 19.69, 26.07, 25.5, 23.69, 26.79, 25.61, 25.06, 24.93, 
22.96, 20.69, 23.97, 24.64, 25.93, 23.69, 25.38, 22.68, 23.36, 
22.44, 22.57, 19.81, 21.19, 20.39, 21.12, 21.89, 29.97, 27.39, 
23.11, 21.75, 20.89, 22.83, 22.02, 20.07, 20.15, 21.24, 19.63, 
23.58, 21.65, 25.17, 23.25, 32.52, 22.59, 30.18, 34.42, 21.86, 
23.99, 24.81, 21.68, 21.04, 23.12, 20.76, 23.13, 22.35, 22.28, 
23.55, 19.85, 26.51, 24.78, 33.73, 30.18, 23.31, 24.51, 25.37, 
23.67, 24.28, 25.82, 21.93, 23.38, 23.07, 25.21, 23.25, 22.93, 
26.86, 21.26, 25.43, 24.54, 27.79, 23.58, 27.56, 23.76, 22.01, 
22.34, 21.07), ssf = c(109.1, 102.8, 104.6, 126.4, 80.3, 75.2, 
87.2, 97.9, 75.1, 65.1, 171.1, 76.8, 117.8, 90.2, 97.2, 99.9, 
125.9, 69.9, 98, 96.8, 80.3, 74.9, 83, 91, 76.2, 52.6, 111.1, 
110.7, 74.7, 113.5, 99.8, 80.3, 109.5, 123.6, 91.2, 49, 110.2, 
89, 98.3, 122.1, 90.4, 106.9, 156.6, 101.1, 126.4, 114, 70, 77, 
148.9, 80.1, 156.6, 115.9, 181.7, 71.6, 143.5, 200.8, 68.9, 103.6, 
71.3, 54.6, 88.2, 95.4, 47.5, 55.6, 62.9, 52.5, 62.6, 49.9, 57.9, 
109.6, 98.5, 136.3, 103.6, 102.8, 131.9, 33.8, 43.5, 46.2, 73.9, 
36.8, 67, 41.1, 59.4, 48.4, 50, 54.6, 42.3, 46.1, 46.3, 109, 
98.1, 80.6, 68.3, 47.6, 61.9, 38.2, 43.5, 56.8, 41.6, 58.9, 44.5, 
41.8, 33.7, 50.9, 40.5, 51.2, 54.4, 52.3, 57, 65.3, 52, 42.7, 
35.2, 49.2, 61.8, 46.5, 34.8, 60.2, 48.1, 44.5, 54, 44.7, 64.9, 
43.8, 58.3, 52.8, 43.1, 78, 40.8, 41.5, 50.9, 49.6, 88.9, 48.3, 
61.8, 43, 61.1, 43.8, 54.2, 41.8, 34.1, 30.5, 34, 46.7, 71.1, 
65.9, 34.3, 34.6, 31.8, 34.5, 31, 32.6, 31.5, 32.6, 31, 28, 33.7, 
30.3, 38, 55.7, 37.5, 112.5, 82.7, 29.7, 38.9, 44.8, 30.9, 44, 
37.5, 37.6, 31.7, 36.6, 48, 41.9, 30.9, 52.8, 43.2, 113.5, 96.9, 
49.3, 42.3, 96.3, 56.5, 105.7, 100.7, 56.8, 75.9, 52.8, 47.8, 
76, 61.2, 75.6, 43.3, 49.5, 70, 75.7, 57.7, 67.2, 56.5, 47.6, 
60.4, 34.9), pcBfat = c(19.75, 21.3, 19.88, 23.66, 17.64, 15.58, 
19.99, 22.43, 17.95, 15.07, 28.83, 18.08, 23.3, 17.71, 18.77, 
19.83, 25.16, 18.04, 21.79, 22.25, 16.25, 16.38, 19.35, 19.2, 
17.89, 12.2, 23.7, 24.69, 16.58, 21.47, 20.12, 17.51, 23.7, 22.39, 
20.43, 11.29, 25.26, 19.39, 19.63, 23.11, 16.86, 21.32, 26.57, 
17.93, 24.97, 22.62, 15.01, 18.14, 26.78, 17.22, 26.5, 23.01, 
30.1, 13.93, 26.65, 35.52, 15.59, 19.61, 14.52, 11.47, 17.71, 
18.48, 11.22, 13.61, 12.78, 11.85, 13.35, 11.77, 11.07, 21.3, 
20.1, 24.88, 19.26, 19.51, 23.01, 8.07, 11.05, 12.39, 15.95, 
9.91, 16.2, 9.02, 14.26, 10.48, 11.64, 12.16, 10.53, 10.15, 10.74, 
20.86, 19.64, 17.07, 15.31, 11.07, 12.92, 8.45, 10.16, 12.55, 
9.1, 13.46, 8.47, 7.68, 6.16, 8.56, 6.86, 9.4, 9.17, 8.54, 9.2, 
11.72, 8.44, 7.19, 6.46, 9, 12.61, 9.03, 6.96, 10.05, 9.56, 9.36, 
10.81, 8.61, 9.53, 7.42, 9.79, 8.97, 7.49, 11.95, 7.35, 7.16, 
8.77, 9.56, 14.53, 8.51, 10.64, 7.06, 8.87, 7.88, 9.2, 7.19, 
6.06, 5.63, 6.59, 9.5, 13.97, 11.66, 6.43, 6.99, 6, 6.56, 6.03, 
6.33, 6.82, 6.2, 5.93, 5.8, 6.56, 6.76, 7.22, 8.51, 7.72, 19.94, 
13.91, 6.1, 7.52, 9.56, 6.06, 7.35, 6, 6.92, 6.33, 5.9, 8.84, 
8.94, 6.53, 9.4, 8.18, 17.41, 18.08, 9.86, 7.29, 18.72, 10.12, 
19.17, 17.24, 9.89, 13.06, 8.84, 8.87, 14.69, 8.64, 14.98, 7.82, 
8.97, 11.63, 13.49, 10.25, 11.79, 10.05, 8.51, 11.5, 6.26), lbm = c(63.32, 
58.55, 55.36, 57.18, 53.2, 53.77, 60.17, 48.33, 54.57, 53.42, 
68.53, 61.85, 48.32, 66.24, 57.92, 56.52, 54.78, 56.31, 62.96, 
56.68, 62.39, 63.05, 56.05, 53.65, 65.45, 64.62, 60.05, 56.48, 
41.54, 52.78, 52.72, 61.29, 59.59, 61.7, 62.46, 53.14, 47.09, 
53.44, 48.78, 56.05, 56.45, 53.11, 54.41, 55.97, 51.62, 58.27, 
57.28, 57.3, 54.18, 42.96, 54.46, 57.2, 54.38, 57.58, 61.46, 
53.46, 54.11, 55.35, 55.39, 52.23, 59.33, 61.63, 63.39, 60.22, 
55.73, 48.57, 51.99, 51.17, 57.54, 68.86, 63.04, 63.03, 66.85, 
59.89, 72.98, 45.23, 55.06, 46.96, 53.54, 47.57, 54.63, 46.31, 
49.13, 53.71, 53.11, 46.12, 53.41, 51.48, 53.2, 56.58, 56.01, 
46.52, 51.75, 42.15, 48.76, 41.93, 42.95, 38.3, 34.36, 39.03, 
61, 69, 74, 80, 78, 71, 71, 78, 77, 81, 66, 77, 91, 78, 75, 78, 
87, 78, 79, 79, 48, 82, 82, 82, 83, 88, 83, 78, 85, 73, 82, 79, 
97, 90, 90, 74, 82, 72, 76, 70, 57, 67, 67, 70, 88, 83, 74, 62, 
67, 70, 64, 58, 57, 73, 54, 67, 66, 75, 78, 102, 74, 78, 106, 
68, 77, 69, 66, 62, 65, 62, 66, 67, 65, 63, 59, 86, 87, 89, 80, 
68, 69, 77, 68, 77, 71, 72, 74, 68, 85, 75, 78, 86, 69, 79, 80, 
82, 68, 82, 72, 68, 63, 72), ht = c(195.9, 189.7, 177.8, 185, 
184.6, 174, 186.2, 173.8, 171.4, 179.9, 193.4, 188.7, 169.1, 
177.9, 177.5, 179.6, 181.3, 179.7, 185.2, 177.3, 179.3, 175.3, 
174, 183.3, 184.7, 180.2, 180.2, 176, 156, 179.7, 180.9, 179.5, 
178.9, 182.1, 186.3, 176.8, 172.6, 176, 169.9, 183, 178.2, 177.3, 
174.1, 173.6, 173.7, 178.7, 183.3, 174.4, 173.3, 168.6, 174, 
176, 172.2, 182.7, 180.5, 179.8, 179.6, 171.7, 170, 170, 180.5, 
173.3, 173.5, 181, 175, 170.3, 165, 169.8, 174.1, 175, 171.1, 
172.7, 175.6, 171.6, 172.3, 171.4, 178, 162, 167.3, 162, 170.8, 
163, 166.1, 176, 163.9, 173, 177, 168, 172, 167.9, 177.5, 162.5, 
172.5, 166.7, 175, 157.9, 158.9, 156.9, 148.9, 149, 172.7, 176.5, 
183, 194.4, 193.4, 180.2, 183, 184, 192.7, 187.2, 183.9, 192, 
190.4, 190.7, 181.8, 188.3, 198, 186, 192, 185.6, 165.3, 185.6, 
189, 193.4, 185.6, 194.6, 189, 188.1, 200.4, 195.3, 194.1, 187.9, 
209.4, 203.4, 198.7, 187.1, 196.6, 186.1, 192.8, 195.2, 169.1, 
186.6, 184.4, 187.3, 185.1, 185.5, 184.9, 175, 185.4, 181, 176, 
176.2, 174, 191, 171, 174, 180.2, 178.5, 190.3, 185, 189, 180.1, 
189.2, 182.6, 186, 174.9, 180.6, 178.6, 173, 179.7, 174.6, 178, 
178.5, 171.3, 178, 189.1, 195.4, 179.1, 180.1, 179.6, 174.7, 
192.7, 179.3, 197.5, 182.7, 190.5, 191, 179.6, 192.6, 194.1, 
193, 193.9, 187.7, 185.3, 191.5, 184.6, 179.9, 183.9, 183.5, 
183.1, 178.4, 190.8), wt = c(78.9, 74.4, 69.1, 74.9, 64.6, 63.7, 
75.2, 62.3, 66.5, 62.9, 96.3, 75.5, 63, 80.5, 71.3, 70.5, 73.2, 
68.7, 80.5, 72.9, 74.5, 75.4, 69.5, 66.4, 79.7, 73.6, 78.7, 75, 
49.8, 67.2, 66, 74.3, 78.1, 79.5, 78.5, 59.9, 63, 66.3, 60.7, 
72.9, 67.9, 67.5, 74.1, 68.2, 68.8, 75.3, 67.4, 70, 74, 51.9, 
74.1, 74.3, 77.8, 66.9, 83.8, 82.9, 64.1, 68.8, 64.8, 59, 72.1, 
75.6, 71.4, 69.7, 63.9, 55.1, 60, 58, 64.7, 87.5, 78.9, 83.9, 
82.8, 74.4, 94.8, 49.2, 61.9, 53.6, 63.7, 52.8, 65.2, 50.9, 57.3, 
60, 60.1, 52.5, 59.7, 57.3, 59.6, 71.5, 69.7, 56.1, 61.1, 47.4, 
56, 45.8, 47.8, 43.8, 37.8, 45.1, 67, 74.4, 79.3, 87.5, 83.5, 
78, 78, 85, 84.7, 92, 72.3, 83, 96.9, 85.7, 85.4, 85.3, 93.5, 
86.8, 87.9, 87.2, 53.8, 89.8, 91.1, 88.6, 92.3, 97, 89.5, 88.2, 
92.2, 78.9, 90.3, 87, 113.7, 98, 100.2, 79.4, 90.3, 77.7, 83.9, 
75.5, 60.6, 71, 71.8, 76.8, 102.7, 94.2, 79, 66.6, 71.8, 74.8, 
68.2, 62.3, 61, 77.5, 57.4, 71.4, 70.3, 80.2, 84.2, 111.3, 80.7, 
97.9, 123.2, 72.9, 83, 75.9, 70.7, 67.1, 69.2, 67.1, 70.5, 70.8, 
71, 69.1, 62.9, 94.8, 94.6, 108.2, 97.9, 75.2, 74.8, 94.2, 76.1, 
94.7, 86.2, 79.6, 85.3, 74.4, 93.5, 87.6, 85.4, 101, 74.9, 87.3, 
90, 94.7, 76.3, 93.2, 80, 73.8, 71.1, 76.7), sex = structure(c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), .Label = c("f", "m"), class = "factor"), 
    sport = structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
    5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 
    5, 5, 5, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 
    4, 4, 4, 4, 4, 4, 4, 6, 6, 6, 6, 6, 6, 6, 6, 6, 2, 7, 2, 
    2, 2, 2, 2, 2, 7, 8, 7, 7, 7, 7, 7, 7, 7, 8, 7, 7, 8, 8, 
    9, 9, 9, 9, 9, 9, 9, 3, 3, 3, 3, 6, 6, 6, 6, 6, 6, 6, 6, 
    6, 6, 6, 6, 6, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 
    5, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 7, 7, 7, 7, 2, 2, 
    2, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 2, 2, 2, 2, 2, 8, 8, 
    8, 7, 7, 7, 7, 8, 8, 7, 8, 7, 8, 2, 2, 2, 2, 8, 10, 10, 10, 
    10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 9, 
    9, 9, 9), .Label = c("B_Ball", "Field", "Gym", "Netball", 
    "Row", "Swim", "T_400m", "T_Sprnt", "Tennis", "W_Polo"), class = "factor")), .Names = c("rcc", 
"wcc", "hc", "hg", "ferr", "bmi", "ssf", "pcBfat", "lbm", "ht", 
"wt", "sex", "sport"), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
"47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", 
"58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", 
"69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79", 
"80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90", 
"91", "92", "93", "94", "95", "96", "97", "98", "99", "100", 
"101", "102", "103", "104", "105", "106", "107", "108", "109", 
"110", "111", "112", "113", "114", "115", "116", "117", "118", 
"119", "120", "121", "122", "123", "124", "125", "126", "127", 
"128", "129", "130", "131", "132", "133", "134", "135", "136", 
"137", "138", "139", "140", "141", "142", "143", "144", "145", 
"146", "147", "148", "149", "150", "151", "152", "153", "154", 
"155", "156", "157", "158", "159", "160", "161", "162", "163", 
"164", "165", "166", "167", "168", "169", "170", "171", "172", 
"173", "174", "175", "176", "177", "178", "179", "180", "181", 
"182", "183", "184", "185", "186", "187", "188", "189", "190", 
"191", "192", "193", "194", "195", "196", "197", "198", "199", 
"200", "201", "202"))
"angina" <-
structure(list(placebo = c(155, 269, 408, 308, 135, 409, 455, 
182, 141, 104, 207, 198, 274, 191, 155, 458, 188, 258, 437, 115, 
200), TNG = c(431, 259, 446, 349, 175, 523, 488, 227, 102, 231, 
249, 247, 397, 251, 401, 766, 199, 566, 552, 237, 387)), .Names = c("placebo", 
"TNG"), row.names = c("1", "2", "3", "4", "5", "6", "7", "8", 
"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", 
"20", "21"), class = "data.frame")
"austpop" <-
structure(list(Year = c(1917, 1927, 1937, 1947, 1957, 1967, 1977, 
1987, 1997), NSW = c(1904, 2402, 2693, 2985, 3625, 4295, 5002, 
5617, 6274), Vic. = c(1409, 1727, 1853, 2055, 2656, 3274, 3837, 
4210, 4605), Qld = c(683, 873, 993, 1106, 1413, 1700, 2130, 2675, 
3401), SA = c(440, 565, 589, 646, 873, 1110, 1286, 1393, 1480
), WA = c(306, 392, 457, 502, 688, 879, 1204, 1496, 1798), Tas. = c(193, 
211, 233, 257, 326, 375, 415, 449, 474), NT = c(5, 4, 6, 11, 
21, 62, 104, 158, 187), ACT = c(3, 8, 11, 17, 38, 103, 214, 265, 
310), Aust. = c(4941, 6182, 6836, 7579, 9640, 11799, 14192, 16264, 
18532)), .Names = c("Year", "NSW", "Vic.", "Qld", "SA", "WA", 
"Tas.", "NT", "ACT", "Aust."), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9"))
"dewpoint" <-
structure(list(maxtemp = c(18, 18, 20, 20, 20, 20, 22, 22, 22, 
22, 22, 24, 24, 24, 24, 24, 24, 26, 26, 26, 26, 26, 26, 28, 28, 
28, 28, 28, 28, 28, 28, 30, 30, 30, 30, 30, 30, 30, 30, 32, 32, 
32, 32, 32, 32, 32, 32, 34, 34, 34, 34, 34, 34, 34, 36, 36, 36, 
36, 36, 36, 36, 38, 38, 38, 38, 38, 38, 40, 40, 40, 40, 40), 
    mintemp = c(8, 10, 6, 8, 10, 12, 8, 10, 12, 14, 16, 8, 10, 
    12, 14, 16, 18, 10, 12, 14, 16, 18, 20, 10, 12, 14, 16, 18, 
    20, 22, 24, 12, 14, 16, 18, 20, 22, 24, 26, 12, 14, 16, 18, 
    20, 22, 24, 26, 14, 16, 18, 20, 22, 24, 26, 14, 16, 18, 20, 
    22, 24, 26, 16, 18, 20, 22, 24, 26, 18, 20, 22, 24, 26), 
    dewpoint = c(7, 10, 5, 7, 9, 12, 6, 9, 11, 14, 16, 5, 8, 
    10, 13, 15, 18, 7, 9, 12, 14, 17, 20, 5, 8, 11, 13, 16, 19, 
    22, 24, 7, 9, 12, 14, 18, 20, 23, 26, 5, 8, 11, 13, 16, 19, 
    22, 25, 6, 9, 12, 15, 18, 21, 25, 5, 7, 10, 13, 16, 19, 22, 
    5, 7, 10, 13, 17, 20, 5, 8, 11, 14, 17)), .Names = c("maxtemp", 
"mintemp", "dewpoint"), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
"47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", 
"58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", 
"69", "70", "71", "72"))
"dolphins" <-
structure(list(wt = c(35, 42, 71, 65, 63, 64, 45, 54, 59, 50, 
42, 55, 37, 47, 40, 52), heart = c(245, 255, 525, 425, 425, 440, 
350, 300, 350, 320, 240, 305, 220, 310, 210, 350), logweight = c(3.55534806148941, 
3.73766961828337, 4.26267987704132, 4.17438726989564, 4.14313472639153, 
4.15888308335967, 3.80666248977032, 3.98898404656427, 4.07753744390572, 
3.91202300542815, 3.73766961828337, 4.00733318523247, 3.61091791264422, 
3.85014760171006, 3.68887945411394, 3.95124371858143), logheart = c(5.50125821054473, 
5.54126354515843, 6.26339826259162, 6.05208916892442, 6.05208916892442, 
6.08677472691231, 5.85793315448346, 5.7037824746562, 5.85793315448346, 
5.76832099579377, 5.48063892334199, 5.72031177660741, 5.39362754635236, 
5.73657229747919, 5.34710753071747, 5.85793315448346), species = c("styx", 
"styx", "styx", "styx", "styx", "styx", "styx", "delph", "delph", 
"delph", "delph", "delph", "delph", "delph", "delph", "delph"
)), .Names = c("wt", "heart", "logweight", "logheart", "species"
), row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", 
"10", "11", "12", "13", "14", "15", "16"), class = "data.frame")
"elasticband" <-
structure(list(stretch = c(46, 54, 48, 50, 44, 42, 52), distance = c(148, 
182, 173, 166, 109, 141, 166)), .Names = c("stretch", "distance"
), row.names = c("1", "2", "3", "4", "5", "6", "7"), class = "data.frame")
"hills" <-
structure(list(distance = c(2.5, 6, 6, 7.5, 8, 8, 16, 6, 5, 6, 
28, 5, 9.5, 6, 4.5, 10, 14, 3, 4.5, 5.5, 3, 3.5, 6, 2, 3, 4, 
6, 5, 6.5, 5, 10, 6, 18, 4.5, 20), climb = c(650, 2500, 900, 
800, 3070, 2866, 7500, 800, 800, 650, 2100, 2000, 2200, 500, 
1500, 3000, 2200, 350, 1000, 600, 300, 1500, 2200, 900, 600, 
2000, 800, 950, 1750, 500, 4400, 600, 5200, 850, 5000), time = c(16.083, 
48.35, 33.65, 45.6, 62.267, 73.217, 204.617, 36.367, 29.75, 39.75, 
192.667, 43.05, 65, 44.133, 26.933, 72.25, 98.417, 78.65, 17.417, 
32.567, 15.95, 27.9, 47.633, 17.933, 18.683, 26.217, 34.433, 
28.567, 50.5, 20.95, 85.583, 32.383, 170.25, 28.1, 159.833)), .Names = c("distance", 
"climb", "time"), class = "data.frame", row.names = c("Greenmantle", 
"Carnethy", "Craig Dunain", "Ben Rha", "Ben Lomond", "Goatfell", 
"Bens of Jura", "Cairnpapple", "Scolty", "Traprain", "Lairig Ghru", 
"Dollar", "Lomonds", "Cairn Table", "Eildon Two", "Cairngorm", 
"Seven Hills", "Knock Hill", "Black Hill", "Creag Beag", "Kildcon Hill", 
"Meall Ant-Suidhe", "Half Ben Nevis", "Cow Hill", "N Berwick Law", 
"Creag Dubh", "Burnswark", "Largo Law", "Criffel", "Acmony", 
"Ben Nevis", "Knockfarrel", "Two Breweries", "Cockleroi", "Moffat Chase"
))
"huron" <-
structure(list(year = c(1860, 1861, 1862, 1863, 1864, 1865, 1866, 
1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 
1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 
1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 
1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 
1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 
1922, 1923, 1924, 1925, 1926, 1927, 1928, 1929, 1930, 1931, 1932, 
1933, 1934, 1935, 1936, 1937, 1938, 1939, 1940, 1941, 1942, 1943, 
1944, 1945, 1946, 1947, 1948, 1949, 1950, 1951, 1952, 1953, 1954, 
1955, 1956, 1957, 1958, 1959, 1960, 1961, 1962, 1963, 1964, 1965, 
1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973, 1974, 1975, 1976, 
1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986), 
    mean.height = c(581.56, 581.55, 581.34, 580.84, 580.33, 580.35, 
    579.87, 580.49, 579.91, 580.07, 580.91, 581.1, 579.72, 580.32, 
    580.48, 580.38, 581.86, 580.97, 580.8, 579.79, 580.39, 580.42, 
    580.82, 581.4, 581.32, 581.44, 581.68, 581.17, 580.53, 580.01, 
    579.91, 579.14, 579.16, 579.55, 579.67, 578.44, 578.24, 579.1, 
    579.09, 579.35, 578.82, 579.32, 579.01, 579, 579.8, 579.83, 
    579.72, 579.89, 580.01, 579.37, 578.69, 578.19, 578.67, 579.55, 
    578.92, 578.09, 579.37, 580.13, 580.14, 579.51, 579.24, 578.66, 
    578.86, 578.05, 577.79, 576.75, 576.75, 577.82, 578.64, 580.58, 
    579.48, 577.38, 576.9, 576.94, 576.24, 576.84, 576.85, 576.9, 
    577.79, 578.18, 577.51, 577.23, 578.42, 579.61, 579.05, 579.26, 
    579.22, 579.38, 579.1, 577.95, 578.12, 579.75, 580.85, 580.41, 
    579.96, 579.61, 578.76, 578.18, 577.21, 577.13, 579.1, 578.25, 
    577.91, 576.89, 575.96, 576.8, 577.68, 578.38, 578.52, 579.74, 
    579.31, 579.89, 579.96, 580.98, 581.04, 580.49, 580.52, 578.57, 
    578.96, 579.94, 579.77, 579.44, 578.97, 580.08, 580.23, 580.75, 
    581.27)), .Names = c("year", "mean.height"), row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
"47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", 
"58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", 
"69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79", 
"80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90", 
"91", "92", "93", "94", "95", "96", "97", "98", "99", "100", 
"101", "102", "103", "104", "105", "106", "107", "108", "109", 
"110", "111", "112", "113", "114", "115", "116", "117", "118", 
"119", "120", "121", "122", "123", "124", "125", "126", "127"
), class = "data.frame")
"ironslag" <-
structure(list(chemical = c(24, 16, 24, 18, 18, 10, 14, 16, 18, 
20, 21, 20, 21, 15, 16, 15, 17, 19, 16, 15, 15, 13, 24, 22, 21, 
24, 15, 20, 20, 25, 27, 22, 20, 24, 24, 23, 29, 27, 23, 19, 25, 
15, 16, 27, 27, 30, 29, 26, 25, 25, 32, 28, 25), magnetic = c(25, 
22, 17, 21, 20, 13, 16, 14, 19, 10, 23, 20, 19, 15, 16, 16, 12, 
15, 15, 15, 15, 17, 18, 16, 18, 22, 20, 21, 21, 21, 25, 22, 18, 
21, 18, 20, 25, 20, 18, 19, 16, 16, 16, 26, 28, 28, 30, 32, 28, 
36, 40, 33, 33)), .Names = c("chemical", "magnetic"), row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
"47", "48", "49", "50", "51", "52", "53"), class = "data.frame")
"islandcities" <-
structure(list(country = structure(c(3, 4, 7, 1, 1, 3, 4, 7, 
2, 4, 3, 5, 5, 4, 4, 3, 4, 6, 1), .Label = c("Australia", "Cuba", 
"Indonesia", "Japan", "Philippines", "Taiwan", "United Kingdom"
), class = "factor"), Population = c(9.4, 8.1, 6.9, 3.7, 3.2, 
2.7, 2.6, 2.6, 2.2, 2.1, 1.9, 1.8, 1.8, 1.7, 1.5, 1.5, 1.5, 1.4, 
1.4)), .Names = c("country", "Population"), class = "data.frame", row.names = c("Jakarta", 
"Tokyo", "London", "Sydney", "Melbourne", "Surabaya", "Osaka", 
"Manchester", "Havana", "Nagoya", "Bandung", "Quezon City", "Manila", 
"Sapporo", "Kobe", "Semarang", "Kyoto", "Gaoxiong", "Brisbane"
))
"kiwishade" <-
structure(list(yield = c(101.11, 108.02, 106.67, 100.3, 92.64, 
103.49, 100.68, 93.42, 100.31, 97, 98.05, 100.74, 105.77, 101.41, 
97.6, 97.42, 103.1, 102.52, 104.02, 104.74, 108.87, 103.14, 108.32, 
101.89, 86.65, 90.75, 87.06, 84.12, 92.17, 93.81, 94.76, 94.05, 
85.4, 81.43, 93.94, 94.91, 92.58, 93.45, 90.29, 91.82, 87.27, 
94.99, 89.06, 90.31, 92.45, 97.57, 97.15, 96.35), block = structure(c(2, 
2, 2, 2, 3, 3, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3, 2, 2, 2, 2, 1, 1, 
1, 1, 3, 3, 3, 3, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 
3, 1, 1, 1, 1), .Label = c("east", "north", "west"), class = "factor"), 
    shade = structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 
    2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 
    3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4), .Label = c("none", 
    "Aug2Dec", "Dec2Feb", "Feb2May"), class = "factor"), plot = structure(c(8, 
    8, 8, 8, 12, 12, 12, 12, 4, 4, 4, 4, 9, 9, 9, 9, 5, 5, 5, 
    5, 1, 1, 1, 1, 10, 10, 10, 10, 6, 6, 6, 6, 2, 2, 2, 2, 7, 
    7, 7, 7, 11, 11, 11, 11, 3, 3, 3, 3), .Label = c("east.Aug2Dec", 
    "east.Dec2Feb", "east.Feb2May", "east.none", "north.Aug2Dec", 
    "north.Dec2Feb", "north.Feb2May", "north.none", "west.Aug2Dec", 
    "west.Dec2Feb", "west.Feb2May", "west.none"), class = "factor")), .Names = c("yield", 
"block", "shade", "plot"), row.names = c("1", "2", "3", "4", 
"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", 
"16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", 
"27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37", 
"38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48"
), class = "data.frame")
"leafshape" <-
structure(list(BladeLen = c(33.88, 33.32, 29.35, 26.87, 26.67, 
24.23, 23.85, 23.3, 23.11, 23.08, 22.14, 21.57, 21.3, 20.97, 
20.82, 20.48, 20.42, 20.41, 20.37, 20.13, 20.04, 19.37, 19.34, 
19.3, 19.21, 19.02, 18.56, 18.34, 18.19, 18.17, 18.07, 17.6, 
17.51, 17.26, 17.26, 17.22, 17.02, 16.8, 16.06, 15.94, 15.92, 
15.58, 15.46, 15.02, 14.92, 14.54, 14.08, 13.75, 13.74, 13.59, 
13.27, 13.07, 13.02, 13.02, 12.99, 12.87, 12.65, 12.28, 12.03, 
11, 10.4, 10.02, 9.81, 8.42, 2.28, 43.4, 41.39, 33.35, 29.34, 
29.25, 28.48, 27.38, 26.6, 24.88, 24.8, 23.75, 22.05, 20.36, 
19.88, 19.35, 6.74, 7.7, 7.97, 8.82, 9.44, 9.92, 11.23, 11.26, 
11.29, 12.12, 12.26, 12.33, 12.92, 13, 13.56, 14.57, 14.58, 14.6, 
15.12, 15.2, 15.67, 16.18, 16.62, 16.71, 17.1, 17.63, 17.69, 
18.7, 19.1, 19.29, 19.99, 20.25, 20.87, 21.16, 26.99, 28.94, 
45.23, 45.89, 20.92, 22.87, 25.94, 14.24, 16.25, 49.3, 24.18, 
14.58, 49.45, 13.8, 14.03, 25.8, 14.79, 28.94, 18.35, 11.67, 
13.11, 7.77, 10.31, 11.28, 11.67, 13.38, 14.1, 14.1, 14.18, 15.01, 
16.1, 16.56, 16.59, 16.86, 17.01, 17.86, 18.01, 18.1, 18.71, 
18.75, 19.74, 20.1, 20.16, 20.32, 20.35, 20.42, 22.67, 22.9, 
23.8, 23.87, 24.7, 26.4, 28.12, 30.06, 28.37, 17.33, 17.68, 18, 
19.21, 20.18, 21.02, 22.44, 26.87, 30.8, 31.95, 32.84, 33.29, 
38.22, 46.6, 46.94, 72.3, 6.93, 7.27, 7.43, 8, 8.08, 8.48, 8.56, 
8.72, 9.15, 9.35, 9.48, 9.56, 10.06, 10.06, 10.11, 10.37, 10.44, 
10.5, 10.55, 10.87, 11.22, 11.66, 11.86, 12.23, 12.84, 12.9, 
12.96, 13.03, 13.4, 13.41, 13.59, 14.36, 14.4, 14.6, 14.9, 16.49, 
16.67, 17.04, 19.89, 24.43, 30.35, 13.98, 14.45, 15.25, 15.3, 
15.35, 15.46, 15.56, 17, 17.8, 17.97, 18.76, 19.68, 20.98, 22.22, 
22.64, 25.28, 26.55, 26.99, 35.84, 42.28, 0.86, 2.08, 6.22, 6.9, 
7.16, 8.03, 8.16, 8.41, 9.66, 11.08, 11.39, 11.46, 11.92, 4.24, 
7.22, 8.23, 9.54, 9.7, 10.01, 10.8, 11.46, 11.87, 11.94, 12.38, 
12.6, 12.68, 13.84, 16.92, 21.9, 29.5, 36.52, 1.15, 6.03, 3.79, 
4.95, 16.65, 4.13, 12.9, 1.12, 1.48), BladeWid = c(13.65, 10.26, 
12.21, 8.7, 8.41, 7.7, 5.69, 8.41, 7.95, 6.98, 8.01, 8.67, 6.59, 
6.73, 6.71, 6.06, 8.48, 6.24, 5.07, 6.73, 5.01, 6.62, 6.57, 7.18, 
6.89, 7.44, 6.22, 5.6, 9.28, 8.32, 6.18, 5.43, 5.85, 4.5, 6.3, 
5.67, 5.6, 5.93, 6.07, 6.6, 6.21, 4.54, 5.51, 4.62, 4.43, 5.01, 
5.37, 5.19, 5.94, 5.62, 5.13, 5.52, 4.85, 4.7, 5.26, 4.97, 5.18, 
5.51, 2.33, 3.79, 3.52, 3.23, 2.82, 2.53, 1.25, 10.94, 17.75, 
12.27, 10.05, 10.42, 7.42, 26.41, 7.25, 7.75, 9.15, 7.14, 8.61, 
6.08, 6.08, 6.96, 2.48, 3.14, 2.63, 3.78, 3.95, 4.11, 4.11, 5.22, 
4.17, 4.03, 5.45, 3.72, 3.81, 3.65, 4.15, 4.88, 5.85, 6.18, 6.42, 
6.13, 6.25, 4.05, 5.8, 4.37, 4.85, 4.8, 6.28, 7.13, 8.32, 7.08, 
6.65, 7.27, 8.21, 7.13, 10.34, 8.43, 16.67, 43.58, 15.09, 14.81, 
16.56, 7.22, 5.64, 26.25, 10.8, 4.5, 11.54, 6.58, 5.4, 7.12, 
3.37, 8.84, 6.99, 4.67, 4.68, 3.31, 2.62, 4.7, 2.82, 3.75, 4.92, 
5.59, 5.3, 5.81, 5.77, 4.78, 6.29, 4.62, 7.97, 6.18, 8.05, 6.57, 
5.58, 5.96, 7.33, 6.31, 8.14, 10.01, 10.29, 4.79, 7.49, 9, 8.37, 
9.34, 10.59, 8.56, 7.31, 9.02, 15.84, 7.2, 5.42, 4.12, 9.34, 
10.13, 7.24, 13.09, 13.59, 10.14, 36.62, 11, 10.54, 15.72, 46.17, 
15.8, 20.6, 3.1, 2.5, 2.98, 3.06, 3.03, 4.33, 4.82, 4.88, 3.01, 
4.04, 3.24, 2.84, 3.37, 3.79, 3.72, 3.48, 3.99, 3.33, 5.16, 4.01, 
4.65, 3.62, 4.33, 4.11, 4.36, 4.18, 4.03, 3.29, 5.59, 4.34, 5.64, 
4.26, 3.98, 3.05, 4.57, 7.61, 5.68, 6.86, 7.81, 6.96, 6.78, 3.9, 
5.72, 3, 5.88, 4.84, 5.85, 4.72, 7.22, 5.28, 6.15, 7.19, 8.16, 
6.58, 11.46, 3.8, 6.85, 5.92, 8.53, 9.51, 23.45, 0.55, 0.79, 
3.2, 2.86, 3.26, 4.02, 3.33, 2.66, 3.44, 4.48, 4.69, 3.42, 5.08, 
1.54, 2.93, 3.05, 4, 2.93, 3.31, 3.57, 5.04, 6.68, 3.05, 3.36, 
4.04, 3.28, 4.3, 3.47, 23.65, 20, 30.57, 0.89, 2.75, 1.51, 2.13, 
3.73, 1.16, 2.55, 0.42, 0.14), Petiole = c(1.403, 1.016, 2.392, 
0.809, 0.803, 1.49, 1.092, 1.911, 1.881, 0.976, 3.015, 2.623, 
1.461, 1.361, 0.885, 0.971, 1.223, 0.957, 0.996, 1.345, 1.178, 
1.586, 1.089, 1.328, 0.851, 0.886, 0.95, 0.673, 0.617, 0.369, 
0.719, 0.627, 1.592, 0.573, 0.917, 0.61, 0.745, 1.324, 1.232, 
0.544, 0.603, 0.499, 0.759, 0.787, 0.971, 0.657, 0.189, 0.553, 
0.988, 0.355, 0.759, 0.714, 0.577, 0.172, 1.982, 0.719, 0.663, 
0.382, 0.48, 0.424, 0.859, 0.351, 0.36, 0.227, 0.113, 3.377, 
5.542, 3.232, 3.227, 4.431, 4.93, 22.16, 1.256, 3.302, 3.867, 
2.503, 4.589, 2.692, 3.211, 3.044, 0.22, 0.39, 0.287, 0.38, 0.435, 
0.293, 0.522, 0.507, 0.291, 0.566, 0.606, 0.491, 0.576, 0.311, 
0.974, 0.884, 1.257, 0.87, 0.511, 0.427, 1.091, 0.608, 0.301, 
1.567, 0.539, 1.65, 1.076, 1.042, 2.277, 1.323, 1.747, 1.221, 
0.885, 0.51, 1.35, 1.276, 3.523, 51.08, 12.924, 11.147, 11.406, 
5.707, 4.254, 9.717, 2.464, 1.433, 4.831, 1.317, 1.225, 1.92, 
0.932, 1.722, 0.789, 0.394, 0.291, 0.478, 0.282, 1.047, 0.532, 
0.587, 0.376, 0.561, 0.727, 1.342, 0.857, 0.623, 0.642, 1.713, 
1.558, 0.511, 1.621, 1.09, 0.975, 0.756, 2.497, 0.748, 1.068, 
2.284, 2.792, 1.062, 1.274, 1.33, 0.702, 1.282, 2.011, 0.908, 
1.167, 1.569, 6.769, 3.398, 1.462, 1.008, 12.235, 1.951, 2.825, 
8.59, 12.656, 2.402, 24.93, 5.451, 2.863, 2.633, 48.88, 3.375, 
2.393, 0.449, 0.262, 0.766, 0.593, 0.493, 0.819, 0.598, 0.59, 
0.521, 0.893, 0.24, 0.66, 1.26, 0.603, 0.745, 0.281, 0.49, 0.1, 
1, 0.848, 1.104, 0.871, 0.856, 0.386, 0.89, 0.271, 0.415, 0.288, 
1.478, 0.855, 0.97, 0.549, 0.451, 1.048, 0.931, 1.205, 0.698, 
1.16, 1.18, 1.204, 1.659, 1.51, 2.884, 0.84, 1.874, 1.805, 1.843, 
1.039, 0.415, 1.556, 3.521, 1.876, 6.593, 3.269, 10.474, 0.875, 
3.635, 2.635, 3.836, 3.799, 1.494, 0.069, 0.129, 0.432, 0.25, 
0.34, 0.662, 0.537, 0.278, 0.682, 1.039, 0.751, 0.599, 0.724, 
0.316, 0.89, 0.285, 0.997, 0.775, 0.907, 0.951, 3.051, 5.789, 
0.528, 0.664, 0.727, 0.905, 1.201, 0.658, 21.35, 0.856, 30.18, 
0.159, 0.482, 0.489, 0.604, 1.407, 0.397, 1.152, 0.134, 0.093
), Lat = c(5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 
5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 
5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 
5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 
9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 
9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 
9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 
9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 9.1, 
9.1, 9.1, 9.1, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 
10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 
10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 
10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 
10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 10.4, 17.1, 17.1, 
17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 
17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 
17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 
17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 
17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 17.1, 
17.1, 17.1, 17.1, 17.1, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 
28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 
28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 28.2, 
28.2, 28.2, 42, 42, 42, 42, 42, 42, 42, 42, 42), site = structure(c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 
5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 
5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6), .Label = c("Sabah", "Panama", 
"Costa Rica", "N Queensland", "S Queensland", "Tasmania"), class = "factor"), 
    arch = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 
    1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
    1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
    1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 
    1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 
    1, 1, 1, 1)), .Names = c("BladeLen", "BladeWid", "Petiole", 
"Lat", "site", "arch"), row.names = c("1", "2", "3", "4", "5", 
"6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", 
"17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", 
"28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", 
"39", "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", 
"50", "51", "52", "53", "54", "55", "56", "57", "58", "59", "60", 
"61", "62", "63", "64", "65", "66", "67", "68", "69", "70", "71", 
"72", "73", "74", "75", "76", "77", "78", "79", "80", "81", "82", 
"83", "84", "85", "86", "87", "88", "89", "90", "91", "92", "93", 
"94", "95", "96", "97", "98", "99", "100", "101", "102", "103", 
"104", "105", "106", "107", "108", "109", "110", "111", "112", 
"113", "114", "115", "116", "117", "118", "119", "120", "121", 
"122", "123", "124", "125", "126", "127", "128", "129", "130", 
"131", "132", "133", "134", "135", "136", "137", "138", "139", 
"140", "141", "142", "143", "144", "145", "146", "147", "148", 
"149", "150", "151", "152", "153", "154", "155", "156", "157", 
"158", "159", "160", "161", "162", "163", "164", "165", "166", 
"167", "168", "169", "170", "171", "172", "173", "174", "175", 
"176", "177", "178", "179", "180", "181", "182", "183", "184", 
"185", "186", "187", "188", "189", "190", "191", "192", "193", 
"194", "195", "196", "197", "198", "199", "200", "201", "202", 
"203", "204", "205", "206", "207", "208", "209", "210", "211", 
"212", "213", "214", "215", "216", "217", "218", "219", "220", 
"221", "222", "223", "224", "225", "226", "227", "228", "229", 
"230", "231", "232", "233", "234", "235", "236", "237", "238", 
"239", "240", "241", "242", "243", "244", "245", "246", "247", 
"248", "249", "250", "251", "252", "253", "254", "255", "256", 
"257", "258", "259", "260", "261", "262", "263", "264", "265", 
"266", "267", "268", "269", "270", "271", "272", "273", "274", 
"275", "276", "277", "278", "279", "280", "281", "282", "283", 
"284", "285", "286"), class = "data.frame")
"moths" <-
structure(list(meters = c(25, 37, 109, 10, 133, 26, 4, 3, 3, 
27, 16, 6, 17, 3, 5, 163, 10, 5, 13, 63, 4, 4, 33, 241, 18, 2, 
182, 48, 20, 3, 36, 233, 44, 35, 8, 55, 6, 90, 44, 21, 36), A = c(9, 
3, 7, 0, 9, 3, 0, 0, 0, 39, 7, 12, 6, 2, 1, 5, 2, 2, 23, 10, 
5, 6, 2, 4, 2, 3, 4, 3, 3, 1, 3, 6, 1, 9, 10, 2, 0, 6, 0, 0, 
9), P = c(8, 20, 9, 2, 1, 18, 5, 5, 2, 5, 16, 0, 0, 0, 0, 1, 
4, 0, 6, 12, 0, 5, 1, 1, 0, 1, 2, 3, 4, 0, 1, 3, 1, 0, 0, 0, 
2, 2, 4, 4, 1), habitat = structure(c(5, 7, 3, 3, 8, 2, 2, 2, 
2, 5, 7, 3, 3, 3, 3, 8, 4, 2, 5, 7, 3, 3, 3, 8, 4, 2, 8, 4, 6, 
6, 6, 8, 4, 6, 6, 6, 2, 4, 4, 1, 6), .Label = c("Bank", "Disturbed", 
"Lowerside", "NEsoak", "NWsoak", "SEsoak", "SWsoak", "Upperside"
), class = "factor")), .Names = c("meters", "A", "P", "habitat"
), class = "data.frame", row.names = c("1", "2", "3", "4", "5", 
"6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", 
"17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", 
"28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", 
"39", "40", "41"))
"oddbooks" <-
structure(list(thick = c(14, 15, 18, 23, 24, 25, 28, 28, 29, 
30, 36, 44), height = c(30.5, 29.1, 27.5, 23.2, 21.6, 23.5, 19.7, 
19.8, 17.3, 22.8, 17.8, 13.5), width = c(23, 20.5, 18.5, 15.2, 
14, 15.5, 12.6, 12.6, 10.5, 15.4, 11, 9.2), weight = c(1075, 
940, 625, 400, 550, 600, 450, 450, 300, 690, 400, 250)), .Names = c("thick", 
"height", "width", "weight"), row.names = c("1", "2", "3", "4", 
"5", "6", "7", "8", "9", "10", "11", "12"), class = "data.frame")
"orings" <-
structure(list(Temperature = c(53, 57, 58, 63, 66, 67, 67, 67, 
68, 69, 70, 70, 70, 70, 72, 73, 75, 75, 76, 76, 78, 79, 81), 
    Erosion = c(3, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0), Blowby = c(2, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0), Total = c(5, 
    1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 
    0, 0, 0)), .Names = c("Temperature", "Erosion", "Blowby", 
"Total"), class = "data.frame", row.names = c("1", "2", "3", 
"4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", 
"16", "17", "18", "19", "20", "21", "22", "23"))
"possum" <-
structure(list(case = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 
29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 
45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 
61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 
77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 
93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104), site = structure(c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 
5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 
6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7), .Label = c("1", 
"2", "3", "4", "5", "6", "7"), class = "factor"), Pop = structure(c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2), .Label = c("Vic", 
"other"), class = "factor"), sex = structure(c(2, 1, 1, 1, 1, 
1, 2, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 
1, 2, 1, 1, 2, 1, 2, 2, 2, 2, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 
2, 2, 1, 1, 2, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 2, 2, 
2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 1, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2, 1), .Label = c("f", 
"m"), class = "factor"), age = c(8, 6, 6, 6, 2, 1, 2, 6, 9, 6, 
9, 5, 5, 3, 5, 4, 1, 2, 5, 4, 3, 3, 4, 2, 3, 7, 2, 4, 3, 2, 3, 
4, 3, 2, 4, 7, 2, 7, 1, 3, 5, 3, 2, NA, 3, NA, 2, 5, 4, 5, 5, 
6, 3, 7, 2, 3, 4, 3, 2, 2, 7, 3, 6, 3, 5, 3, 4, 5, 5, 7, 6, 1, 
1, 4, 6, 5, 6, 1, 1, 1, 3, 4, 3, 3, 3, 3, 2, 2, 6, 3, 3, 2, 3, 
7, 4, 4, 3, 5, 3, 1, 1, 6, 4, 3), hdlngth = c(94.1, 92.5, 94, 
93.2, 91.5, 93.1, 95.3, 94.8, 93.4, 91.8, 93.3, 94.9, 95.1, 95.4, 
92.9, 91.6, 94.7, 93.5, 94.4, 94.8, 95.9, 96.3, 92.5, 94.4, 95.8, 
96, 90.5, 93.8, 92.8, 92.1, 92.8, 94.3, 91.4, 90.6, 94.4, 93.3, 
89.3, 92.4, 84.7, 91, 88.4, 85.3, 90, 85.1, 90.7, 91.4, 90.1, 
98.6, 95.4, 91.6, 95.6, 97.6, 93.1, 96.9, 103.1, 99.9, 95.1, 
94.5, 102.5, 91.3, 95.7, 91.3, 92, 96.9, 93.5, 90.4, 93.3, 94.1, 
98, 91.9, 92.8, 85.9, 82.5, 88.7, 93.8, 92.4, 93.6, 86.5, 85.8, 
86.7, 90.6, 86, 90, 88.4, 89.5, 88.2, 98.5, 89.6, 97.7, 92.6, 
97.8, 90.7, 89.2, 91.8, 91.6, 94.8, 91, 93.2, 93.3, 89.5, 88.6, 
92.4, 91.5, 93.6), skullw = c(60.4, 57.6, 60, 57.1, 56.3, 54.8, 
58.2, 57.6, 56.3, 58, 57.2, 55.6, 59.9, 57.6, 57.6, 56, 67.7, 
55.7, 55.4, 56.3, 58.1, 58.5, 56.1, 54.9, 58.5, 59, 54.5, 56.8, 
56, 54.4, 54.1, 56.7, 54.6, 55.7, 57.9, 59.3, 54.8, 56, 51.5, 
55, 57, 54.1, 55.5, 51.5, 55.9, 54.4, 54.8, 63.2, 59.2, 56.4, 
59.6, 61, 58.1, 63, 63.2, 61.5, 59.4, 64.2, 62.8, 57.7, 59, 58, 
56.4, 56.5, 57.4, 55.8, 57.6, 56, 55.6, 56.4, 57.6, 52.4, 52.3, 
52, 58.1, 56.8, 56.2, 51, 50, 52.6, 56, 54, 53.8, 54.6, 56.2, 
53.2, 60.7, 58, 58.4, 54.6, 59.6, 56.3, 54, 57.6, 56.6, 55.7, 
53.1, 68.6, 56.2, 56, 54.7, 55, 55.2, 59.9), totlngth = c(89, 
91.5, 95.5, 92, 85.5, 90.5, 89.5, 91, 91.5, 89.5, 89.5, 92, 89.5, 
91.5, 85.5, 86, 89.5, 90, 90.5, 89, 96.5, 91, 89, 84, 91.5, 90, 
85, 87, 88, 84, 93, 94, 89, 85.5, 85, 88, 82.5, 80.5, 75, 84.5, 
83, 77, 81, 76, 81, 84, 89, 85, 85, 88, 85, 93.5, 91, 91.5, 92.5, 
93.7, 93, 91, 96, 88, 86, 90.5, 88.5, 89.5, 88.5, 86, 85, 88.5, 
88, 87, 90, 80.5, 82, 83, 89, 89, 84, 81, 81, 84, 85.5, 82, 81.5, 
80.5, 92, 86.5, 93, 87.5, 84.5, 85, 89, 85, 82, 84, 88.5, 83, 
86, 84, 86.5, 81.5, 82.5, 89, 82.5, 89), taillgth = c(36, 36.5, 
39, 38, 36, 35.5, 36, 37, 37, 37.5, 39, 35.5, 36, 36, 34, 34.5, 
36.5, 36, 35, 38, 39.5, 39.5, 36, 34, 35.5, 36, 35, 34.5, 35, 
33.5, 37, 39, 37, 36.5, 35.5, 35, 35, 35.5, 34, 36, 36.5, 32, 
32, 35.5, 34, 35, 37.5, 34, 37, 38, 36, 40, 38, 43, 38, 38, 41, 
39, 40, 39, 38, 39, 38, 38.5, 38, 36.5, 36.5, 38, 37.5, 38, 40, 
35, 36.5, 38, 38, 41, 36, 36.5, 36.5, 38, 38, 36.5, 36, 36, 40.5, 
38.5, 41.5, 38, 35, 38.5, 38, 37, 38, 35.5, 37.5, 38, 38, 35, 
38.5, 36.5, 39, 38, 36.5, 40), footlgth = c(74.5, 72.5, 75.4, 
76.1, 71, 73.2, 71.5, 72.7, 72.4, 70.9, 77.2, 71.7, 71, 74.3, 
69.7, 73, 73.2, 73.7, 73.4, 73.8, 77.9, 73.5, 72.8, 75, 72.3, 
73.6, 70.3, 73.2, 74.9, 70.6, 68, 74.8, 70.8, 73.1, 71.2, 74.3, 
71.2, 68.4, 68.7, 72.8, NA, 62.7, 72, 70.3, 71.5, 72.8, 66, 66.9, 
69, 65, 64, 67.9, 67.4, 71.3, 72.5, 68.7, 67.2, 66.5, 73.2, 63.1, 
63.1, 65.5, 64.1, 63, 68.2, 63.2, 64.7, 65.9, 65, 65.4, 65.7, 
62, 65.7, 61.5, 66.2, 64.5, 62.8, 63, 62.8, 62.3, 65.6, 60.7, 
62, 62.6, 65.6, 60.3, 71.7, 66.7, 64.4, 69.8, 65.5, 67.6, 63.8, 
64.2, 64.5, 66.5, 63.8, 65.6, 64.8, 66, 64.4, 63.5, 62.9, 67.6
), earconch = c(54.5, 51.2, 51.9, 52.2, 53.2, 53.6, 52, 53.9, 
52.9, 53.4, 51.3, 51, 49.8, 53.7, 51.8, 51.4, 53.2, 55.4, 53.9, 
52.4, 52.9, 52.1, 53.3, 53.5, 51.6, 56.2, 50.8, 53, 51.8, 50.8, 
52.5, 52, 51.8, 53.1, 55.5, 52, 52, 49.5, 53.4, 51.4, 40.3, 51.2, 
49.4, 52.6, 54, 51.2, 45.5, 44.9, 45, 47.2, 43.9, 44.3, 46, 46, 
44.9, 46.8, 45.3, 46.4, 44.5, 47, 44.9, 41.3, 46.3, 45.1, 41.7, 
44.2, 44.1, 43.1, 45.6, 44.1, 42.8, 42.4, 44.7, 45.9, 45.6, 46.4, 
42.9, 44.3, 43, 44.8, 41.7, 42.9, 43.3, 43.6, 43.5, 43.7, 46.8, 
43.5, 46.2, 44.8, 48, 46.8, 44.9, 45.1, 45.4, 47.7, 46, 44.3, 
43.8, 46.8, 48, 45.4, 45.9, 46), eye = c(15.2, 16, 15.5, 15.2, 
15.1, 14.2, 14.2, 14.5, 15.5, 14.4, 14.9, 15.3, 15.8, 15.1, 15.7, 
14.4, 14.7, 15.3, 15.2, 15.5, 14.2, 16.2, 15.4, 16.2, 14.9, 15, 
14.2, 15.3, 14, 14.5, 14.5, 14.9, 14.8, 14.4, 16.4, 14.9, 13.6, 
15.9, 13, 13.6, 15.9, 13.8, 13.4, 14.4, 14.6, 14.4, 15, 17, 15.9, 
14.9, 17.4, 15.8, 16.5, 17.5, 16.4, 16.4, 14.5, 14.4, 14.7, 14.4, 
15, 16, 15.2, 17.1, 14, 15.7, 16.5, 17.4, 15, 13, 15, 14.1, 16, 
14.7, 16.9, 17.8, 16.2, 13.2, 14.8, 15, 17, 15.4, 14, 16.3, 14.5, 
13.6, 15, 16, 14.4, 14.5, 15, 14.5, 12.8, 14.4, 14.9, 14, 14.5, 
14.5, 14, 14.8, 14, 13, 15.4, 14.8), chest = c(28, 28.5, 30, 
28, 28.5, 30, 30, 29, 28, 27.5, 31, 28, 27, 28, 28, 28, 29, 28, 
28, 27, 30, 28, 28, 27, 31, 29, 23, 27, 24, 24.5, 27, 28, 24, 
26, 28, 25.5, 28, 27, 25, 27, 27, 25.5, 29, 23, 27, 24.5, 25, 
28, 29.5, 28, 28, 28.5, 26, 30, 30.5, 27.5, 31, 30.5, 32, 26, 
26.5, 27, 25.5, 25.5, 29, 26.5, 27.5, 27, 28.5, 27, 27.5, 25.5, 
23.5, 26, 26, 26, 25, 23, 22, 23.5, 27.5, 26, 25, 25, 27, 26, 
26, 25.5, 29, 25.5, 26, 25.5, 24, 29, 27, 25, 25, 28.5, 28, 23, 
25, 25, 25, 28.5), belly = c(36, 33, 34, 34, 33, 32, 34.5, 34, 
33, 32, 34, 33, 32, 31.5, 35, 32, 31, 32, 32, 36, 40, 36, 35, 
32, 35, 38, 28, 30, 32, 33, 31, 34, 30, 28.5, 35.5, 36, 31.5, 
30, 25, 30, 30.5, 33, 31, 27, 31.5, 35, 33, 35, 35.5, 36, 38.5, 
32.5, 33.5, 36.5, 36, 31.5, 39, 33, 36, 30, 31, 32, 28.5, 33, 
38.5, 34, 29.5, 30, 34, 34, 34, 30, 28, 34, 33.5, 33, 35, 28, 
28.5, 30.5, 35, 32, 29, 28.5, 31.5, 31, 36, 31.5, 30.5, 32.5, 
32, 31, 31, 35, 31, 33, 31.5, 32, 35, 27, 33, 30, 29, 33.5)), .Names = c("case", 
"site", "Pop", "sex", "age", "hdlngth", "skullw", "totlngth", 
"taillgth", "footlgth", "earconch", "eye", "chest", "belly"), row.names = c("C3", 
"C5", "C10", "C15", "C23", "C24", "C26", "C27", "C28", "C31", 
"C32", "C34", "C36", "C37", "C39", "C40", "C45", "C47", "C48", 
"C50", "C54", "C55", "C58", "C59", "C60", "C61", "C63", "C64", 
"A1", "A2", "A3", "A4", "AD1", "BB4", "BB13", "BB15", "BB17", 
"BB25", "BB31", "BB33", "BB36", "BB38", "BB40", "BB41", "BB44", 
"BB45", "WW1", "WW2", "WW3", "WW4", "WW5", "WW6", "WW7", "BR1", 
"BR2", "BR3", "BR4", "BR5", "BR6", "BR7", "CD1", "CD2", "CD3", 
"CD4", "CD5", "CD6", "CD7", "CD8", "CD9", "CD10", "CD11", "CD12", 
"CD13", "BSF1", "BSF2", "BSF3", "BSF4", "BSF5", "BSF6", "BSF7", 
"BSF8", "BSF9", "BSF10", "BSF11", "BSF12", "BSF13", "BTP1", "BTP3", 
"BTP4", "BTP5", "BTP6", "BTP7", "BTP8", "BTP9", "BTP10", "BTP12", 
"BTP13", "BTP14", "BTP15", "BTP16", "BTP17", "BTP19", "BTP20", 
"BTP21"), class = "data.frame")
"primates" <-
structure(list(Species = structure(c(4, 2, 3, 5, 1), .Label = c("Chimp", 
"Gorilla", "Human", "Potar monkey", "Rhesus monkey"), class = "factor"), 
    Bodywt = c(10, 207, 62, 6.8, 52.2), Brainwt = c(115, 406, 
    1320, 179, 440)), .Names = c("Species", "Bodywt", "Brainwt"
), class = "data.frame", row.names = c("1", "2", "3", "4", "5"
))
"rainforest" <-
structure(list(dbh = c(6, 23, 20, 23, 24, 5, 5, 8, 10, 8, 22, 
9, 10, 10, 19, 35, 6, 4, 4, 6, 5, 8, 6, 5, 7, 5, 7, 6, 25, 24, 
31, 21, 16, 27, 19, 21, 10, 23, 27, 26, 9, 12, 9, 11, 10, 37, 
37, 20, 56, 9, 17, 17, 10, 6, 22, 15, 15, 19, 11, 9, 25, 22, 
10, 12, 48), wood = c(NA, 353, 208, 445, 590, 14, 10, 31, 59, 
30, 320, 20, 29, 35, 203, 1090, 10, 7, 3, 13, 9, 20, 16, 7, 29, 
12, 25, 10, 506, 508, 817, 274, 162, 540, 272, 293, 77, 408, 
550, 414, 42, 85, 35, 60, 60, 1250, 990, 290, 1500, 40, 216, 
208, 50, 18, 382, 161, 140, 280, 84, 50, 510, 400, 70, 115, 1530
), bark = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 105, 78, 8, 13, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA), root = c(6, 135, NA, NA, NA, 2, NA, NA, NA, 
6, 51, 6, NA, 9, 16, 66, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 44, 38, 5, 
17, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA), rootsk = c(0.3, 13, NA, NA, 
NA, 2.4, NA, NA, NA, 1, 17, 1, NA, 2, 11, 24, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, 9, 13, 1.3, 2.2, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), branch = c(NA, 
35, 41, 50, NA, NA, NA, NA, NA, 4, 30, 13, 10, 17, 46, 92, 11, 
6, 5, 5, 8, 9, 6, 8, 14, 8, 16, 9, 45, 65, 95, 31, 25, 55, 52, 
NA, NA, NA, 59, 44, 7, 16, 9, 13, 12, 76, 90, 36, NA, NA, 40, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, 45, 35, NA, NA, 120), species = structure(c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 
4, 4, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
3), .Label = c("Acacia mabellae", "C. fraseri", "Acmena smithii", 
"B. myrtifolia"), class = "factor")), .Names = c("dbh", "wood", 
"bark", "root", "rootsk", "branch", "species"), class = "data.frame", row.names = c("27", 
"61", "62", "63", "65", "80", "81", "82", "83", "84", "95", "96", 
"97", "98", "99", "100", "102", "103", "104", "105", "106", "107", 
"108", "109", "110", "111", "112", "113", "114", "115", "116", 
"117", "118", "119", "120", "121", "122", "123", "124", "125", 
"126", "127", "128", "129", "130", "131", "132", "133", "134", 
"135", "136", "137", "138", "139", "140", "141", "142", "143", 
"144", "145", "146", "147", "148", "149", "150"))
"seedrates" <-
structure(list(rate = c(50, 75, 100, 125, 150), grain = c(21.2, 
19.9, 19.2, 18.4, 17.9)), .Names = c("rate", "grain"), row.names = c("1", 
"2", "3", "4", "5"), class = "data.frame")
"soi" <-
structure(list(rain = c(553, 460, 399, 470, 448, 395, 556, 614, 
453, 389, 545, 582, 439, 422, 426, 431, 440, 441, 381, 388, 499, 
440, 395, 452, 464, 363, 417, 396, 381, 497, 394, 502, 525, 423, 
385, 417, 404, 532, 400, 513, 658, 373, 395, 474, 483, 599, 635, 
408, 447, 441, 491, 362, 457, 481, 452, 362, 409, 440, 578, 435, 
395, 528, 372, 686, 797, 619, 576, 491, 551, 484, 449, 560, 424, 
520, 584, 415, 425, 470, 464, 520, 435, 482, 467), soi = c(12.1, 
-5.2, -8.2, -6, -13.2, -10.6, 7.1, 19.8, 0.9, -9.1, 1.9, 1.6, 
4.1, -2.7, 4.3, -1.6, -3.6, -1, 4.5, 4.8, 0.5, -0.7, -8.5, 1.8, 
0.3, 1.7, 0.5, 1.2, 8.7, 0.5, -13.4, -12.4, 1.3, 4.1, -1.9, 4.3, 
-6.4, 2.1, -1.2, -1, 14.6, -0.8, -2.4, -6.7, 3.9, 10.2, 10.2, 
-3.9, -3.4, -0.1, 3.5, 0.8, 5.2, -2.1, 5.7, -8, -4.1, 3, 2.8, 
-5.3, 3.8, 10.3, -7.1, 7, 9.3, 12.9, 1, -9.4, -1.8, -1.9, -2.9, 
1.7, -12.7, -8, -0.1, 0.7, -2.7, -12.3, 7.6, 6.2, -2.3, -8.5, 
-9.9), year = c(1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 
1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925, 1926, 1927, 1928, 
1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937, 1938, 1939, 
1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949, 1950, 
1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961, 
1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 
1973, 1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 
1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992)), .Names = c("rain", 
"soi", "year"), row.names = c("1", "2", "3", "4", "5", "6", "7", 
"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", 
"19", "20", "21", "22", "23", "24", "25", "26", "27", "28", "29", 
"30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", 
"41", "42", "43", "44", "45", "46", "47", "48", "49", "50", "51", 
"52", "53", "54", "55", "56", "57", "58", "59", "60", "61", "62", 
"63", "64", "65", "66", "67", "68", "69", "70", "71", "72", "73", 
"74", "75", "76", "77", "78", "79", "80", "81", "82", "83"), class = "data.frame")
"tinting" <-
structure(list(case = c(1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 
2, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 
5, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 
8, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 10, 10, 11, 11, 11, 
11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 
13, 13, 14, 14, 14, 14, 14, 14, 14, 15, 15, 15, 15, 15, 15, 15, 
16, 16, 16, 16, 16, 16, 16, 17, 17, 17, 17, 17, 17, 17, 18, 18, 
18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 20, 20, 20, 20, 
20, 20, 20, 21, 21, 21, 21, 21, 21, 21, 22, 22, 22, 22, 22, 22, 
22, 23, 23, 23, 23, 23, 23, 23, 24, 24, 24, 24, 24, 24, 24, 25, 
25, 25, 25, 25, 25, 25, 26, 26, 26, 26, 26, 26, 26), id = c(1, 
1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 5, 
5, 5, 5, 5, 5, 5, 11, 11, 11, 11, 11, 11, 11, 13, 13, 13, 13, 
13, 13, 13, 15, 15, 15, 15, 15, 15, 15, 16, 16, 16, 16, 16, 16, 
16, 17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 6, 
6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 9, 
9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 10, 10, 21, 21, 21, 21, 
21, 21, 21, 22, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, 23, 23, 
23, 26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 27, 19, 
19, 19, 19, 19, 19, 19, 25, 25, 25, 25, 25, 25, 25, 28, 28, 28, 
28, 28, 28, 28, 12, 12, 12, 12, 12, 12, 12, 24, 24, 24, 24, 24, 
24, 24, 14, 14, 14, 14, 14, 14, 14), age = c(22.4, 22.4, 22.4, 
22.4, 22.4, 22.4, 22.4, 26.8, 26.8, 26.8, 26.8, 26.8, 26.8, 26.8, 
22.2, 22.2, 22.2, 22.2, 22.2, 22.2, 22.2, 22.6, 22.6, 22.6, 22.6, 
22.6, 22.6, 22.6, 23.1, 23.1, 23.1, 23.1, 23.1, 23.1, 23.1, 27.3, 
27.3, 27.3, 27.3, 27.3, 27.3, 27.3, 22.2, 22.2, 22.2, 22.2, 22.2, 
22.2, 22.2, 27.8, 27.8, 27.8, 27.8, 27.8, 27.8, 27.8, 22.2, 22.2, 
22.2, 22.2, 22.2, 22.2, 22.2, 21.7, 21.7, 21.7, 21.7, 21.7, 21.7, 
21.7, 70.3, 70.3, 70.3, 70.3, 70.3, 70.3, 70.3, 74.1, 74.1, 74.1, 
74.1, 74.1, 74.1, 74.1, 72.1, 72.1, 72.1, 72.1, 72.1, 72.1, 72.1, 
75.3, 75.3, 75.3, 75.3, 75.3, 75.3, 75.3, 74.7, 74.7, 74.7, 74.7, 
74.7, 74.7, 74.7, 74.3, 74.3, 74.3, 74.3, 74.3, 74.3, 74.3, 76.9, 
76.9, 76.9, 76.9, 76.9, 76.9, 76.9, 74.4, 74.4, 74.4, 74.4, 74.4, 
74.4, 74.4, 75.5, 75.5, 75.5, 75.5, 75.5, 75.5, 75.5, 73.4, 73.4, 
73.4, 73.4, 73.4, 73.4, 73.4, 24.5, 24.5, 24.5, 24.5, 24.5, 24.5, 
24.5, 78.2, 78.2, 78.2, 78.2, 78.2, 78.2, 78.2, 71, 71, 71, 71, 
71, 71, 71, 26.1, 26.1, 26.1, 26.1, 26.1, 26.1, 26.1, 70.4, 70.4, 
70.4, 70.4, 70.4, 70.4, 70.4, 23.2, 23.2, 23.2, 23.2, 23.2, 23.2, 
23.2), sex = structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 
2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 
2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 
1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 
1, 1), .Label = c("f", "m"), class = "factor"), tint = structure(c(1, 
2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 
2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 
2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 
2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 
2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 
2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 
2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 
2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1, 1, 
2, 3, 1, 2, 3, 1, 1, 2, 3, 1, 2, 3, 1), .Label = c("no", "lo", 
"hi"), class = c("ordered", "factor")), target = structure(c(2, 
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2, 2, 
2, 2, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 2), .Label = c("locon", "hicon"
), class = "factor"), it = c(26, 32.24, 27.04, 17.68, 20.8, 26, 
24.96, 21.79, 21.79, 23.86, 24.9, 32.16, 22.83, 24.9, 27.04, 
24.96, 39.52, 40.56, 27.04, 30.16, 21.84, 38.48, 38.48, 29.12, 
34.32, 32.24, 40.56, 35.36, 47.725, 29.05, 38.3875, 46.6875, 
37.35, 38.3875, 33.2, 29.05, 25.9375, 28.0125, 30.0875, 31.125, 
40.4625, 32.1625, 51.88, 79.89, 61.21, 45.65, 57.06, 74.7, 43.58, 
25.9375, 23.8625, 23.8625, 26.975, 37.35, 35.275, 20.75, 34.2375, 
30.0875, 31.125, 35.275, 31.125, 51.875, 23.8625, 32.1625, 31.125, 
40.4625, 42.5375, 57.0625, 43.575, 34.2375, 46.8, 36.4, 46.8, 
43.68, 56.16, 61.36, 48.88, 75.92, 70.72, 101.92, 81.12, 80.08, 
92.56, 75.92, 44.72, 38.48, 75.92, 30.16, 49.92, 67.6, 33.28, 
30.16, 35.36, 34.32, 42.64, 47.84, 42.64, 27.04, 50.96, 48.88, 
56.16, 47.84, 53.04, 141.44, 78, 78.85, 61.2125, 74.7, 57.0625, 
57.0625, 91.3, 47.725, 47.725, 47.725, 51.875, 50.8375, 59.1375, 
67.4375, 60.175, 38.3875, 48.7625, 44.6125, 59.1375, 73.6625, 
57.0625, 35.275, 89.225, 99.6, 120.35, 118.275, 87.15, 135.9125, 
113.0875, 34.2375, 37.35, 47.725, 58.1, 58.1, 79.8875, 28.0125, 
38.39, 42.54, 40.46, 39.43, 39.43, 48.76, 36.31, 140.06, 123.46, 
139.03, 159.78, 146.29, 199.2, 121.39, 135.91, 98.56, 122.43, 
113.09, 120.35, 197.12, 91.3, 78.85, 60.18, 72.63, 51.88, 56.03, 
65.36, 67.44, 174.3, 104.58, 151.48, 169.11, 187.58, 209.58, 
124.5, 41.5, 50.84, 43.58, 53.95, 41.5, 60.18, 36.31), csoa = c(46.8, 
37.44, 42.64, 41.6, 37.44, 40.56, 38.48, 44.61, 50.84, 51.88, 
47.73, 48.76, 57.06, 42.54, 38.48, 32.24, 30.16, 44.72, 36.4, 
33.28, 30.16, 38.48, 35.36, 38.48, 38.48, 33.28, 32.24, 32.24, 
63.2875, 60.175, 60.175, 41.5, 43.575, 54.9875, 47.725, 57.0625, 
66.4, 50.8375, 49.8, 45.65, 47.725, 49.8, 46.6875, 46.6875, 50.8375, 
56.025, 54.9875, 51.875, 44.6125, 35.275, 50.8375, 42.5375, 41.5, 
41.5, 41.5, 29.05, 25.9375, 25.9375, 30.0875, 38.3875, 37.35, 
36.3125, 26.975, 39.425, 42.5375, 43.575, 48.7625, 52.9125, 44.6125, 
41.5, 43.68, 54.08, 41.6, 49.92, 42.64, 46.8, 37.44, 63.44, 61.36, 
62.4, 57.2, 63.44, 65.52, 58.24, 50.96, 37.44, 43.68, 42.64, 
39.52, 45.76, 38.48, 46.8, 47.84, 47.84, 50.96, 48.88, 54.08, 
44.72, 64.48, 54.08, 62.4, 60.32, 63.44, 60.32, 52, 76.775, 73.6625, 
84.0375, 109.975, 89.225, 96.4875, 80.925, 77.8125, 65.3625, 
59.1375, 52.9125, 51.875, 62.25, 44.6125, 38.3875, 40.4625, 41.5, 
53.95, 44.6125, 46.6875, 39.425, 60.175, 40.4625, 58.1, 47.725, 
47.725, 59.1375, 53.95, 42.5375, 38.3875, 38.3875, 48.7625, 42.5375, 
43.575, 44.6125, 39.43, 32.16, 37.35, 30.09, 30.09, 33.2, 25.94, 
74.7, 68.48, 77.81, 77.81, 87.15, 128.65, 61.21, 77.81, 68.48, 
65.36, 68.48, 69.51, 105.83, 53.95, 53.95, 37.35, 41.5, 38.39, 
43.58, 44.61, 46.69, 60.18, 60.18, 68.48, 70.55, 74.7, 84.04, 
51.88, 39.43, 25.94, 36.31, 29.05, 31.13, 26.98, 28.01), agegp = structure(c(1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 
2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 
2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1), .Label = c("young", "elderly"
), class = "factor")), .Names = c("case", "id", "age", "sex", 
"tint", "target", "it", "csoa", "agegp"), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
"47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", 
"58", "59", "60", "61", "62", "63", "64", "65", "66", "67", "68", 
"69", "70", "71", "72", "73", "74", "75", "76", "77", "78", "79", 
"80", "81", "82", "83", "84", "85", "86", "87", "88", "89", "90", 
"91", "92", "93", "94", "95", "96", "97", "98", "99", "100", 
"101", "102", "103", "104", "105", "106", "107", "108", "109", 
"110", "111", "112", "113", "114", "115", "116", "117", "118", 
"119", "120", "121", "122", "123", "124", "125", "126", "127", 
"128", "129", "130", "131", "132", "133", "134", "135", "136", 
"137", "138", "139", "140", "141", "142", "143", "144", "145", 
"146", "147", "148", "149", "150", "151", "152", "153", "154", 
"155", "156", "157", "158", "159", "160", "161", "162", "163", 
"164", "165", "166", "167", "168", "169", "170", "171", "172", 
"173", "174", "175", "176", "177", "178", "179", "180", "181", 
"182"))
"type.df" <-
structure(list(abbrev = c("Sm", "Md", "Cm", "Lr", "-", "Vn", 
"Sp"), Type = c("Small", "Medium", "Compact", "Large", "", "Van", 
"Sporty")), .Names = c("abbrev", "Type"), class = "data.frame", row.names = c("Small", 
"Medium", "Compact", "Large", "NK", "Van", "Sporty"))
"dsetnames" <-
c("ACF", "Cars93.summary", "additions", "ais", "angina", "austpop", 
"dewpoint", "dolphins", "elasticband", "hills", "huron", "ironslag", 
"islandcities", "kiwishade", "leafshape", "moths", "oddbooks", 
"orings", "possum", "primates", "rainforest", "seedrates", "soi", 
"tinting", "type.df", "dsetnames", "Barley", "florida", "anesthetic", 
"milk")
"Barley" <-
structure(list(Site = structure(c(5, 5, 5, 5, 5, 6, 6, 6, 6, 
6, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 2, 2, 2, 2, 2, 
5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 4, 4, 4, 4, 4, 1, 1, 1, 1, 1, 3, 
3, 3, 3, 3, 2, 2, 2, 2, 2), .Label = c("C", "D", "GR", "M", "UF", 
"W"), class = "factor"), Variety = structure(c(1, 3, 5, 4, 2, 
1, 3, 5, 4, 2, 1, 3, 5, 4, 2, 1, 3, 5, 4, 2, 1, 3, 5, 4, 2, 1, 
3, 5, 4, 2, 1, 3, 5, 4, 2, 1, 3, 5, 4, 2, 1, 3, 5, 4, 2, 1, 3, 
5, 4, 2, 1, 3, 5, 4, 2, 1, 3, 5, 4, 2), .Label = c("Manchuria", 
"Peatland", "Svansota", "Trebi", "Velvet"), class = "factor"), 
    Year = c(1931, 1931, 1931, 1931, 1931, 1931, 1931, 1931, 
    1931, 1931, 1931, 1931, 1931, 1931, 1931, 1931, 1931, 1931, 
    1931, 1931, 1931, 1931, 1931, 1931, 1931, 1931, 1931, 1931, 
    1931, 1931, 1932, 1932, 1932, 1932, 1932, 1932, 1932, 1932, 
    1932, 1932, 1932, 1932, 1932, 1932, 1932, 1932, 1932, 1932, 
    1932, 1932, 1932, 1932, 1932, 1932, 1932, 1932, 1932, 1932, 
    1932, 1932), Yield = c(81, 105.4, 119.7, 109.7, 98.3, 146.6, 
    142, 150.7, 191.5, 145.7, 82.3, 77.3, 78.4, 131.3, 89.6, 
    119.8, 121.4, 124, 140.8, 124.8, 98.9, 89, 69.1, 89.3, 104.1, 
    86.9, 77.1, 78.9, 101.8, 96, 80.7, 82.3, 80.4, 87.2, 84.2, 
    100.4, 115.5, 112.2, 147.7, 108.1, 103.1, 105.1, 116.5, 139.9, 
    129.6, 98.9, 61.9, 96.2, 125.5, 75.7, 66.4, 49.9, 96.7, 61.9, 
    80.3, 67.7, 66.7, 67.4, 91.8, 94.1)), .Names = c("Site", 
"Variety", "Year", "Yield"), row.names = c("1", "2", "3", "4", 
"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", 
"16", "17", "18", "19", "20", "21", "22", "23", "24", "25", "26", 
"27", "28", "29", "30", "31", "32", "33", "34", "35", "36", "37", 
"38", "39", "40", "41", "42", "43", "44", "45", "46", "47", "48", 
"49", "50", "51", "52", "53", "54", "55", "56", "57", "58", "59", 
"60"), class = "data.frame")
"florida" <-
structure(list(County = structure(c(1, 2, 3, 4, 5, 6, 7, 8, 9, 
10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 
26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 
42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 58, 59, 55, 
56, 57, 60, 61, 62, 63, 64, 65, 66, 67), .Label = c("ALACHUA", 
"BAKER", "BAY", "BRADFORD", "BREVARD", "BROWARD", "CALHOUN", 
"CHARLOTTE", "CITRUS", "CLAY", "COLLIER", "COLUMBIA", "DADE", 
"DE SOTO", "DIXIE", "DUVAL", "ESCAMBIA", "FLAGLER", "FRANKLIN", 
"GADSDEN", "GILCHRIST", "GLADES", "GULF", "HAMILTON", "HARDEE", 
"HENDRY", "HERNANDO", "HIGHLANDS", "HILLSBOROUGH", "HOLMES", 
"INDIAN RIVER", "JACKSON", "JEFFERSON", "LAFAYETTE", "LAKE", 
"LEE", "LEON", "LEVY", "LIBERTY", "MADISON", "MANATEE", "MARION", 
"MARTIN", "MONROE", "NASSAU", "OKALOOSA", "OKEECHOBEE", "ORANGE", 
"OSCEOLA", "PALM BEACH", "PASCO", "PINELLAS", "POLK", "PUTNAM", 
"SANTA ROSA", "SARASOTA", "SEMINOLE", "ST. JOHNS", "ST. LUCIE", 
"SUMTER", "SUWANNEE", "TAYLOR", "UNION", "VOLUSIA", "WAKULLA", 
"WALTON", "WASHINGTON"), class = c("AsIs", "factor")), V2 = structure(c(38, 
46, 33, 18, 16, 42, 5, 43, 29, 37, 49, 25, 41, 11, 3, 22, 2, 
23, 46, 13, 1, 5, 9, 46, 4, 19, 37, 24, 26, 13, 32, 23, 5, 35, 
47, 12, 48, 18, 46, 3, 8, 49, 31, 31, 18, 34, 17, 20, 44, 39, 
6, 28, 14, 36, 40, 45, 30, 10, 7, 21, 13, 9, 3, 15, 4, 27, 11
), .Label = c(" (100% of 10)", " (100% of 108)", " (100% of 11)", 
" (100% of 12)", " (100% of 13)", " (100% of 132)", " (100% of 133)", 
" (100% of 135)", " (100% of 14)", " (100% of 142)", " (100% of 15)", 
" (100% of 150)", " (100% of 16)", " (100% of 163)", " (100% of 172)", 
" (100% of 177)", " (100% of 18)", " (100% of 21)", " (100% of 22)", 
" (100% of 232)", " (100% of 24)", " (100% of 268)", " (100% of 27)", 
" (100% of 28)", " (100% of 31)", " (100% of 320)", " (100% of 33)", 
" (100% of 345)", " (100% of 35)", " (100% of 36)", " (100% of 40)", 
" (100% of 41)", " (100% of 47)", " (100% of 48)", " (100% of 5)", 
" (100% of 50)", " (100% of 51)", " (100% of 53)", " (100% of 531)", 
" (100% of 57)", " (100% of 614)", " (100% of 618)", " (100% of 63)", 
" (100% of 66)", " (100% of 78)", " (100% of 8)", " (100% of 86)", 
" (100% of 95)", " (100% of 96)"), class = c("AsIs", "factor"
)), GORE = c(47300, 2392, 18850, 3072, 97318, 386518, 2155, 29641, 
25501, 14630, 29905, 7047, 328702, 3322, 1825, 107680, 40958, 
13891, 2042, 9565, 1910, 1420, 2389, 1718, 2341, 3239, 32644, 
14152, 166581, 2154, 19769, 6868, 3038, 788, 36555, 73560, 61425, 
5403, 1011, 3011, 49169, 44648, 26619, 16483, 6952, 16924, 4588, 
140115, 28177, 268945, 69550, 199660, 74977, 12091, 19482, 41559, 
12795, 72854, 58888, 9634, 4084, 2647, 1399, 97063, 3835, 5637, 
2796), BUSH = c(34062, 5610, 38637, 5413, 115185, 177279, 2873, 
35419, 29744, 41745, 60426, 10964, 289456, 4256, 2698, 152082, 
73029, 12608, 2448, 4750, 3300, 1840, 3546, 2153, 3764, 4743, 
30646, 20196, 176967, 4985, 28627, 9138, 2481, 1669, 49963, 106141, 
39053, 6860, 1316, 3038, 57948, 55135, 33864, 16059, 16404, 52043, 
5058, 134476, 26216, 152846, 68581, 184312, 90101, 13439, 39497, 
34705, 36248, 83100, 75293, 12126, 8014, 4051, 2326, 82214, 4511, 
12176, 4983), BUCHANAN = c(262, 73, 248, 65, 570, 789, 90, 182, 
270, 186, 122, 89, 561, 36, 29, 650, 504, 83, 33, 39, 29, 9, 
71, 24, 30, 22, 242, 99, 836, 76, 105, 102, 29, 10, 289, 305, 
282, 67, 39, 29, 272, 563, 108, 47, 90, 267, 43, 446, 145, 3407, 
570, 1010, 538, 147, 229, 124, 311, 305, 194, 114, 108, 27, 26, 
396, 46, 120, 88), NADER = c(3215, 53, 828, 84, 4470, 7099, 39, 
1461, 1378, 562, 1400, 258, 5355, 157, 75, 2752, 1729, 435, 85, 
139, 97, 56, 86, 39, 75, 103, 1501, 409, 7348, 91, 950, 138, 
76, 26, 1459, 3587, 1932, 284, 19, 54, 2489, 1810, 1075, 1090, 
255, 984, 131, 3881, 732, 5564, 3392, 9986, 2060, 379, 1214, 
1368, 723, 4066, 1940, 307, 182, 59, 29, 2436, 149, 265, 93), 
    BROWNE = c(658, 17, 171, 28, 643, 1212, 10, 127, 194, 204, 
    185, 127, 759, 23, 32, 954, 297, 60, 17, 24, 52, 12, 21, 
    11, 17, 11, 116, 51, 1104, 18, 123, 40, 14, 6, 203, 538, 
    330, 92, 12, 18, 243, 361, 105, 162, 63, 313, 21, 892, 309, 
    743, 412, 1222, 365, 114, 210, 165, 131, 431, 551, 53, 53, 
    4, 13, 3211, 30, 68, 32), HAGELIN = c(42, 3, 18, 2, 39, 128, 
    1, 15, 16, 14, 34, 7, 119, 0, 2, 160, 24, 4, 3, 4, 1, 3, 
    4, 2, 2, 1, 26, 14, 215, 7, 13, 2, 1, 0, 36, 81, 28, 1, 3, 
    2, 35, 26, 29, 26, 8, 15, 4, 65, 21, 143, 82, 444, 59, 7, 
    11, 12, 13, 94, 38, 2, 4, 3, 0, 33, 3, 11, 20), HARRIS = c(4, 
    0, 5, 0, 11, 49, 0, 6, 5, 1, 7, 1, 88, 0, 0, 36, 6, 1, 1, 
    7, 0, 0, 2, 6, 0, 3, 8, 5, 35, 1, 4, 0, 2, 3, 4, 30, 9, 1, 
    0, 0, 5, 14, 13, 1, 0, 4, 1, 13, 10, 45, 18, 40, 8, 2, 4, 
    4, 1, 11, 38, 2, 2, 0, 1, 9888, 2, 3, 0), MCREYNOLDS = c(658, 
    0, 3, 0, 11, 35, 1, 3, 0, 3, 4, 2, 36, 3, 0, 16, 3, 3, 0, 
    3, 0, 1, 2, 9, 0, 2, 4, 3, 29, 3, 2, 1, 1, 1, 1, 5, 7, 1, 
    0, 1, 3, 6, 8, 0, 4, 2, 1, 7, 5, 302, 14, 27, 5, 4, 2, 10, 
    1, 5, 5, 0, 0, 1, 0, 3, 1, 2, 0), MOOREHEAD = c(21, 3, 37, 
    3, 76, 123, 3, 12, 28, 9, 29, 5, 124, 2, 2, 41, 20, 12, 2, 
    12, 4, 1, 9, 4, 3, 2, 22, 7, 150, 2, 10, 7, 0, 0, 14, 96, 
    31, 11, 2, 5, 26, 49, 12, 7, 3, 20, 4, 45, 33, 103, 77, 167, 
    36, 12, 13, 29, 19, 59, 70, 17, 5, 1, 0, 59, 6, 18, 5), PHILLIPS = c(20, 
    3, 18, 2, 72, 74, 2, 19, 18, 6, 10, 8, 69, 8, 3, 57, 110, 
    3, 3, 6, 2, 0, 2, 7, 2, 7, 10, 5, 66, 6, 13, 4, 0, 1, 21, 
    34, 16, 10, 1, 1, 19, 22, 19, 3, 3, 33, 3, 41, 10, 188, 17, 
    70, 46, 10, 12, 13, 43, 15, 27, 3, 9, 8, 0, 2927, 0, 7, 9
    ), Total = c(86242, 8154, 58815, 8669, 218395, 573306, 5174, 
    66885, 57154, 57360, 92122, 18508, 625269, 7807, 4666, 264428, 
    116680, 27100, 4634, 14549, 5395, 3342, 6132, 3973, 6234, 
    8133, 65219, 34941, 353331, 7343, 49616, 16300, 5642, 2504, 
    88545, 184377, 103113, 12730, 2403, 6159, 110209, 102634, 
    61852, 33878, 23782, 70605, 9854, 279981, 55658, 432286, 
    142713, 396938, 168195, 26205, 60674, 77989, 50285, 160940, 
    137044, 22258, 12461, 6801, 3794, 198230, 8583, 18307, 8026
    )), .Names = c("County", "V2", "GORE", "BUSH", "BUCHANAN", 
"NADER", "BROWNE", "HAGELIN", "HARRIS", "MCREYNOLDS", "MOOREHEAD", 
"PHILLIPS", "Total"), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
"47", "48", "49", "50", "51", "52", "53", "54", "55", "56", "57", 
"58", "59", "60", "61", "62", "63", "64", "65", "66", "67"))
"anesthetic" <-
structure(list(move = c(0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 0, 
0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0), conc = c(1, 
1.2, 1.4, 1.4, 1.2, 2.5, 1.6, 0.8, 1.6, 1.4, 0.8, 1.6, 2.5, 1.4, 
1.6, 1.4, 1.4, 0.8, 0.8, 1.2, 0.8, 0.8, 1, 0.8, 1, 1.2, 1, 1.2, 
1, 1.2), logconc = c(0, 0.182321556793955, 0.336472236621213, 
0.336472236621213, 0.182321556793955, 0.916290731874155, 0.470003629245736, 
-0.22314355131421, 0.470003629245736, 0.336472236621213, -0.22314355131421, 
0.470003629245736, 0.916290731874155, 0.336472236621213, 0.470003629245736, 
0.336472236621213, 0.336472236621213, -0.22314355131421, -0.22314355131421, 
0.182321556793955, -0.22314355131421, -0.22314355131421, 0, -0.22314355131421, 
0, 0.182321556793955, 0, 0.182321556793955, 0, 0.182321556793955
), nomove = c(1, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 
1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1)), .Names = c("move", 
"conc", "logconc", "nomove"), class = "data.frame", row.names = c("1", 
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
"25", "26", "27", "28", "29", "30"))
"milk" <-
structure(list(four = c(7.2, 7.4, 7, 7.2, 4.6, 6, 5, 4.2, 3.8, 
6.1, 3.7, 3.9, 2.5, 4.4, 4.2, 4.6, 5.6), one = c(5.8, 6.9, 6, 
6, 5.4, 5.7, 6.1, 3.7, 3.8, 4.3, 3.4, 1.4, 1.7, 5.4, 3.2, 2.2, 
3.6)), .Names = c("four", "one"), row.names = c("1", "2", "3", 
"4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", 
"16", "17"), class = "data.frame")
